{"cells":[{"cell_type":"markdown","metadata":{"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"3700F0383ACD456594322246327904AB","mdEditEnable":false},"source":" # 深度卷积神经网络（AlexNet） "},{"cell_type":"markdown","metadata":{"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"E59CD3957F874D2D9FB1B0D7C1A3566C","mdEditEnable":false},"source":"LeNet:  在大的真实数据集上的表现并不尽如人意。     \n1.神经网络计算复杂。  \n2.还没有大量深入研究参数初始化和非凸优化算法等诸多领域。  \n  \n机器学习的特征提取: 手工定义的特征提取函数  \n神经网络的特征提取: 通过学习得到数据的多级表征，并逐级表示越来越抽象的概念或模式。  \n  \n神经网络发展的限制:数据、硬件"},{"attachments":{"1576144713%281%29.png":{"image/png":"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"}},"cell_type":"markdown","metadata":{"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"894A96EBC1404E008C042A83D1A053F9","mdEditEnable":false},"source":"### AlexNet\n首次证明了学习到的特征可以超越手工设计的特征，从而一举打破计算机视觉研究的前状。   \n**特征：**\n1. 8层变换，其中有5层卷积和2层全连接隐藏层，以及1个全连接输出层。\n2. 将(LeNet中的)sigmoid激活函数改成了更加简单的ReLU激活函数。\n3. 用Dropout来控制全连接层的模型复杂度。\n4. 引入数据增强，如翻转、裁剪和颜色变化，从而进一步扩大数据集来缓解过拟合。\n\n![Image Name](https://cdn.kesci.com/upload/image/q5kv4gpx88.png?imageView2/0/w/640/h/640)\n\n\n"},{"cell_type":"code","execution_count":7,"metadata":{"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"DD41B540CFAB491B9D43105C3D90647C","collapsed":false,"scrolled":false},"outputs":[],"source":"#目前GPU算力资源预计17日上线，在此之前本代码只能使用CPU运行。\n#考虑到本代码中的模型过大，CPU训练较慢，\n#我们还将代码上传了一份到 https://www.kaggle.com/boyuai/boyu-d2l-modernconvolutionalnetwork\n#如希望提前使用gpu运行请至kaggle。\n\n\nimport time\nimport torch\nfrom torch import nn, optim\nimport torchvision\nimport numpy as np\nimport sys\nsys.path.append(\"/home/kesci/input/\") \nimport d2lzh1981 as d2l\nimport os\nimport torch.nn.functional as F\n\ndevice = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n\nclass AlexNet(nn.Module):\n    def __init__(self):\n        super(AlexNet, self).__init__()\n        self.conv = nn.Sequential(\n            nn.Conv2d(1, 96, 11, 4), # in_channels, out_channels, kernel_size, stride, padding\n            nn.ReLU(),\n            nn.MaxPool2d(3, 2), # kernel_size, stride\n            # 减小卷积窗口，使用填充为2来使得输入与输出的高和宽一致，且增大输出通道数\n            nn.Conv2d(96, 256, 5, 1, 2),\n            nn.ReLU(),\n            nn.MaxPool2d(3, 2),\n            # 连续3个卷积层，且使用更小的卷积窗口。除了最后的卷积层外，进一步增大了输出通道数。\n            # 前两个卷积层后不使用池化层来减小输入的高和宽\n            nn.Conv2d(256, 384, 3, 1, 1),\n            nn.ReLU(),\n            nn.Conv2d(384, 384, 3, 1, 1),\n            nn.ReLU(),\n            nn.Conv2d(384, 256, 3, 1, 1),\n            nn.ReLU(),\n            nn.MaxPool2d(3, 2)\n        )\n         # 这里全连接层的输出个数比LeNet中的大数倍。使用丢弃层来缓解过拟合\n        self.fc = nn.Sequential(\n            nn.Linear(256*5*5, 4096),\n            nn.ReLU(),\n            nn.Dropout(0.5),\n            #由于使用CPU镜像，精简网络，若为GPU镜像可添加该层\n            #nn.Linear(4096, 4096),\n            #nn.ReLU(),\n            #nn.Dropout(0.5),\n\n            # 输出层。由于这里使用Fashion-MNIST，所以用类别数为10，而非论文中的1000\n            nn.Linear(4096, 10),\n        )\n\n    def forward(self, img):\n\n        feature = self.conv(img)\n        output = self.fc(feature.view(img.shape[0], -1))\n        return output"},{"cell_type":"code","execution_count":8,"metadata":{"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"237401462039416F8B5874A7DA7FD9F2","collapsed":false,"scrolled":false},"outputs":[{"output_type":"stream","text":"AlexNet(\n  (conv): Sequential(\n    (0): Conv2d(1, 96, kernel_size=(11, 11), stride=(4, 4))\n    (1): ReLU()\n    (2): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n    (3): Conv2d(96, 256, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n    (4): ReLU()\n    (5): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n    (6): Conv2d(256, 384, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n    (7): ReLU()\n    (8): Conv2d(384, 384, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n    (9): ReLU()\n    (10): Conv2d(384, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n    (11): ReLU()\n    (12): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n  )\n  (fc): Sequential(\n    (0): Linear(in_features=6400, out_features=4096, bias=True)\n    (1): ReLU()\n    (2): Dropout(p=0.5, inplace=False)\n    (3): Linear(in_features=4096, out_features=10, bias=True)\n  )\n)\n","name":"stdout"}],"source":"net = AlexNet()\nprint(net)"},{"cell_type":"markdown","metadata":{"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"EEF29AB29F37460C84C492FCE02FEF2D","mdEditEnable":false},"source":"### 载入数据集"},{"cell_type":"code","execution_count":9,"metadata":{"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"8994A770DF884A5D87F60737C50D0A1F","collapsed":false,"scrolled":false},"outputs":[{"output_type":"stream","text":"X = torch.Size([8, 1, 224, 224]) \nY = tensor([6, 1, 0, 9, 8, 4, 5, 7], dtype=torch.int32)\n","name":"stdout"}],"source":"# 本函数已保存在d2lzh_pytorch包中方便以后使用\ndef load_data_fashion_mnist(batch_size, resize=None, root='/home/kesci/input/FashionMNIST2065'):\n    \"\"\"Download the fashion mnist dataset and then load into memory.\"\"\"\n    trans = []\n    if resize:\n        trans.append(torchvision.transforms.Resize(size=resize))\n    trans.append(torchvision.transforms.ToTensor())\n    \n    transform = torchvision.transforms.Compose(trans)\n    mnist_train = torchvision.datasets.FashionMNIST(root=root, train=True, download=True, transform=transform)\n    mnist_test = torchvision.datasets.FashionMNIST(root=root, train=False, download=True, transform=transform)\n\n    train_iter = torch.utils.data.DataLoader(mnist_train, batch_size=batch_size, shuffle=True, num_workers=2)\n    test_iter = torch.utils.data.DataLoader(mnist_test, batch_size=batch_size, shuffle=False, num_workers=2)\n\n    return train_iter, test_iter\n\n#batchsize=128\n#batch_size = 16\nbatch_size = 8\n# 如出现“out of memory”的报错信息，可减小batch_size或resize\ntrain_iter, test_iter = load_data_fashion_mnist(batch_size,224)\nfor X, Y in train_iter:\n    print('X =', X.shape,\n        '\\nY =', Y.type(torch.int32))\n    break\n    "},{"cell_type":"markdown","metadata":{"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"B3671547A0D04495B5B1F2ADE856500F","mdEditEnable":false},"source":"### 训练"},{"cell_type":"code","execution_count":4,"metadata":{"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"FB33F7F4BEE1486187254524422FDF80","collapsed":false,"scrolled":false},"outputs":[{"output_type":"stream","text":"training on  cpu\nepoch 1, loss 0.5017, train acc 0.812, test acc 0.863, time 6137.1 sec\n","name":"stdout"}],"source":"#在 CPU上训练的话,时间会非常久\nlr, num_epochs = 0.001, 3\noptimizer = torch.optim.Adam(net.parameters(), lr=lr)\nd2l.train_ch5(net, train_iter, test_iter, batch_size, optimizer, device, num_epochs)"},{"attachments":{"image.png":{"image/png":"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"}},"cell_type":"markdown","metadata":{"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"C40CCB5CDD8E4D3B9A6264B03CBEEB76","mdEditEnable":false},"source":"#  使用重复元素的网络（VGG）\nVGG：通过重复使用简单的基础块来构建深度模型。  比LeNet简单,便于设计新的网络.\nBlock:数个相同的填充为1、窗口形状为$3\\times 3$的卷积层,接上一个步幅为2、窗口形状为$2\\times 2$的最大池化层。  \n卷积层保持输入的高和宽不变，而池化层则对其减半。\n\n\n![Image Name](https://cdn.kesci.com/upload/image/q5l6vut7h1.png?imageView2/0/w/640/h/640)\n中间VGG block的最大池化层应该是$2\\times 2$的\n"},{"cell_type":"markdown","metadata":{"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"F3D1E7D0AC154E6A99842D587608E870","mdEditEnable":false},"source":"### VGG11的简单实现"},{"cell_type":"code","execution_count":4,"metadata":{"collapsed":false,"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"AA4AB087A263436B90B719085FEABC67","scrolled":false},"outputs":[],"source":"\ndef vgg_block(num_convs, in_channels, out_channels): #卷积层个数，输入通道数，输出通道数\n#第一层实现了输入通道数到输出通道数的改变,后边的层保持不变.\n    blk = []\n    for i in range(num_convs):\n        if i == 0:\n            blk.append(nn.Conv2d(in_channels, out_channels, kernel_size=3, padding=1))\n        else:\n            blk.append(nn.Conv2d(out_channels, out_channels, kernel_size=3, padding=1))\n        blk.append(nn.ReLU())\n    blk.append(nn.MaxPool2d(kernel_size=2, stride=2)) # 最大池化层,这里会使宽高减半\n    return nn.Sequential(*blk)"},{"cell_type":"code","execution_count":5,"metadata":{"collapsed":false,"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"3199FD641C1F417FA3C6B65784A20CF2","scrolled":false},"outputs":[],"source":"conv_arch = ((1, 1, 64), (1, 64, 128), (2, 128, 256), (2, 256, 512), (2, 512, 512))\n# 经过5个vgg_block, 宽高会减半5次, 变成 224/32 = 7\nfc_features = 512 * 7 * 7 # c * w * h\nfc_hidden_units = 4096 # 任意"},{"cell_type":"code","execution_count":6,"metadata":{"collapsed":false,"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"08AA6A69F80B4DAC8FA831C6E5C9260B","scrolled":false},"outputs":[],"source":"def vgg(conv_arch, fc_features, fc_hidden_units=4096):\n    net = nn.Sequential()\n    # 卷积层部分\n    for i, (num_convs, in_channels, out_channels) in enumerate(conv_arch):\n        # 每经过一个vgg_block都会使宽高减半\n        net.add_module(\"vgg_block_\" + str(i+1), vgg_block(num_convs, in_channels, out_channels))\n    # 全连接层部分\n    net.add_module(\"fc\", nn.Sequential(d2l.FlattenLayer(),\n                                 nn.Linear(fc_features, fc_hidden_units),\n                                 nn.ReLU(),\n                                 nn.Dropout(0.5),\n                                 nn.Linear(fc_hidden_units, fc_hidden_units),\n                                 nn.ReLU(),\n                                 nn.Dropout(0.5),\n                                 nn.Linear(fc_hidden_units, 10)\n                                ))\n    return net"},{"cell_type":"code","execution_count":7,"metadata":{"collapsed":false,"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"A5FDDE9D6C404D868E3AB5E1731043D9","scrolled":false},"outputs":[],"source":"net = vgg(conv_arch, fc_features, fc_hidden_units)\nX = torch.rand(1, 1, 224, 224)\n\n# named_children获取一级子模块及其名字(named_modules会返回所有子模块,包括子模块的子模块)\nfor name, blk in net.named_children(): \n    X = blk(X)\n    print(name, 'output shape: ', X.shape)"},{"cell_type":"code","execution_count":8,"metadata":{"collapsed":false,"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"40A6F9278D034D4A874189A1F8F52ABF","scrolled":false},"outputs":[],"source":"ratio = 8\nsmall_conv_arch = [(1, 1, 64//ratio), (1, 64//ratio, 128//ratio), (2, 128//ratio, 256//ratio), \n                   (2, 256//ratio, 512//ratio), (2, 512//ratio, 512//ratio)]\nnet = vgg(small_conv_arch, fc_features // ratio, fc_hidden_units // ratio)\nprint(net)"},{"cell_type":"code","execution_count":10,"metadata":{"collapsed":false,"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"5325FD0A7DB64D43809A660129617282","scrolled":false},"outputs":[],"source":"batchsize=16\n#batch_size = 64\n# 如出现“out of memory”的报错信息，可减小batch_size或resize\n# train_iter, test_iter = d2l.load_data_fashion_mnist(batch_size, resize=224)\n\nlr, num_epochs = 0.001, 5\noptimizer = torch.optim.Adam(net.parameters(), lr=lr)\nd2l.train_ch5(net, train_iter, test_iter, batch_size, optimizer, device, num_epochs)"},{"attachments":{"1576145663%281%29.png":{"image/png":"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"}},"cell_type":"markdown","metadata":{"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"7D83E04F316B4D0B933654E2F9FB08B9","mdEditEnable":false},"source":"#  网络中的网络（NiN） \nLeNet、AlexNet和VGG：先以由卷积层构成的模块充分抽取空间特征，再以由全连接层构成的模块来输出分类结果。  \nNiN：串联多个由卷积层和“全连接”层构成的小网络来构建一个深层网络。  \n去掉了LeNet,VGG和AlexNet中用于调整类别数的全连接层,NiN用了输出通道数等于标签类别数的NiN块(基础块)，然后使用全局平均池化层对每个通道中所有元素求平均并直接用于分类。  \n\n![Image Name](https://cdn.kesci.com/upload/image/q5l6u1p5vy.png?imageView2/0/w/960/h/960)\n\n1×1卷积核作用   \n1.放缩通道数：通过控制卷积核的数量达到通道数的放缩。  \n2.增加非线性。1×1卷积核的卷积过程相当于全连接层的计算过程，并且还加入了非线性激活函数，从而可以增加网络的非线性。  \n3.和全连接相比,计算参数少   "},{"cell_type":"code","execution_count":9,"metadata":{"collapsed":false,"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"88FB988FED1F4CB08417E01A3C560459","scrolled":false},"outputs":[],"source":"\ndef nin_block(in_channels, out_channels, kernel_size, stride, padding):\n    blk = nn.Sequential(nn.Conv2d(in_channels, out_channels, kernel_size, stride, padding),\n                        nn.ReLU(),\n                        nn.Conv2d(out_channels, out_channels, kernel_size=1),\n                        nn.ReLU(),\n                        nn.Conv2d(out_channels, out_channels, kernel_size=1),\n                        nn.ReLU())\n    return blk"},{"cell_type":"code","execution_count":10,"metadata":{"collapsed":false,"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"AB1A33FE0F1C451F87F390FEC87D334E","scrolled":false},"outputs":[],"source":"# 已保存在d2lzh_pytorch\nclass GlobalAvgPool2d(nn.Module):\n    # 全局平均池化层可通过将池化窗口形状设置成输入的高和宽实现\n    def __init__(self):\n        super(GlobalAvgPool2d, self).__init__()\n    def forward(self, x):\n        return F.avg_pool2d(x, kernel_size=x.size()[2:])\n\nnet = nn.Sequential(\n    nin_block(1, 96, kernel_size=11, stride=4, padding=0),\n    nn.MaxPool2d(kernel_size=3, stride=2),\n    nin_block(96, 256, kernel_size=5, stride=1, padding=2),\n    nn.MaxPool2d(kernel_size=3, stride=2),\n    nin_block(256, 384, kernel_size=3, stride=1, padding=1),\n    nn.MaxPool2d(kernel_size=3, stride=2), \n    nn.Dropout(0.5),\n    # 标签类别数是10\n    nin_block(384, 10, kernel_size=3, stride=1, padding=1),\n    GlobalAvgPool2d(), \n    # 将四维的输出转成二维的输出，其形状为(批量大小, 10)\n    d2l.FlattenLayer())"},{"cell_type":"code","execution_count":11,"metadata":{"collapsed":false,"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"08C2986CBEEF40F98825FC6FF163C572","scrolled":false},"outputs":[],"source":"X = torch.rand(1, 1, 224, 224)\nfor name, blk in net.named_children(): \n    X = blk(X)\n    print(name, 'output shape: ', X.shape)"},{"cell_type":"code","execution_count":14,"metadata":{"collapsed":false,"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"DBD61B6A08E1400996DCB60B4B570818","scrolled":false},"outputs":[],"source":"batch_size = 128\n# 如出现“out of memory”的报错信息，可减小batch_size或resize\n#train_iter, test_iter = d2l.load_data_fashion_mnist(batch_size, resize=224)\n\nlr, num_epochs = 0.002, 5\noptimizer = torch.optim.Adam(net.parameters(), lr=lr)\nd2l.train_ch5(net, train_iter, test_iter, batch_size, optimizer, device, num_epochs)"},{"cell_type":"markdown","metadata":{"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"AE1E233B008843DEB6E582ECFEE65617","mdEditEnable":false},"source":"NiN重复使用由卷积层和代替全连接层的1×1卷积层构成的NiN块来构建深层网络。  \nNiN去除了容易造成过拟合的全连接输出层，而是将其替换成输出通道数等于标签类别数 的NiN块和全局平均池化层。   \nNiN的以上设计思想影响了后面一系列卷积神经网络的设计。  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"}},"cell_type":"markdown","metadata":{"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"7886126F79424D75863FB4B09025CE40","mdEditEnable":false},"source":"# GoogLeNet\n1. 由Inception基础块组成。  \n2. Inception块相当于一个有4条线路的子网络。它通过不同窗口形状的卷积层和最小池化层来并行抽取信息，并使用1×1卷积层减少通道数从而降低模型复杂度。   \n3. 可以自定义的超参数是每个层的输出通道数，我们以此来控制模型复杂度。 \n\n![Image Name](https://cdn.kesci.com/upload/image/q5l6uortw.png?imageView2/0/w/640/h/640)\n"},{"cell_type":"code","execution_count":12,"metadata":{"collapsed":false,"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"E9CBC745630F489CB69A0001B076F199","scrolled":false},"outputs":[],"source":"\nclass Inception(nn.Module):\n    # c1 - c4为每条线路里的层的输出通道数\n    def __init__(self, in_c, c1, c2, c3, c4):\n        super(Inception, self).__init__()\n        # 线路1，单1 x 1卷积层\n        self.p1_1 = nn.Conv2d(in_c, c1, kernel_size=1)\n        # 线路2，1 x 1卷积层后接3 x 3卷积层\n        self.p2_1 = nn.Conv2d(in_c, c2[0], kernel_size=1)\n        self.p2_2 = nn.Conv2d(c2[0], c2[1], kernel_size=3, padding=1)\n        # 线路3，1 x 1卷积层后接5 x 5卷积层\n        self.p3_1 = nn.Conv2d(in_c, c3[0], kernel_size=1)\n        self.p3_2 = nn.Conv2d(c3[0], c3[1], kernel_size=5, padding=2)\n        # 线路4，3 x 3最大池化层后接1 x 1卷积层\n        self.p4_1 = nn.MaxPool2d(kernel_size=3, stride=1, padding=1)\n        self.p4_2 = nn.Conv2d(in_c, c4, kernel_size=1)\n\n    def forward(self, x):\n        p1 = F.relu(self.p1_1(x))\n        p2 = F.relu(self.p2_2(F.relu(self.p2_1(x))))\n        p3 = F.relu(self.p3_2(F.relu(self.p3_1(x))))\n        p4 = F.relu(self.p4_2(self.p4_1(x)))\n        return torch.cat((p1, p2, p3, p4), dim=1)  # 在通道维上连结输出"},{"attachments":{"1576155704%281%29.png":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAASwAAAIJCAYAAAAf9ABtAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAAHYcAAB2HAY/l8WUAAHVgSURBVHhe7Z0FYBPZFoZ/aIu7u9vitrjLY/HFpbi7u7u7a3F3d5fF3d3dChQoFd78txNoS4GmTdKmOd97s83cO5lMQubPOeeee26or1+/foMgCIIVEFr/KwiCEOwRwRIEwWoQwRIEwWoQwRIEwWoQwRIEwWqQUUIL8e3bN3z58gXu7u56i2ArRIgQAXZ2dvqeEBhEsCzEs2fPkClTJjg7O+stgq3Qt29ftQmBRwTLQjx48ACpUqVC3bp1kSNHDr1VCOl06tQJderUwZw5c/QWITCIYFkIg2AtXrwYjo6OeqsQ0nFwcEDt2rVFsEyEBN0FQbAaRLAEQbAaRLAEQbAaRLAEP2Eaxvv37/Hu3bvvm4uLCzw8PPQjBMHyiGAJfsKcsVKlSqFAgQIoXrw4ChcurP6WL18eBw4cgJubm36kIFgOESzhl3z48AETJ07E/v37sW/fPixfvhy1atVSo5xz587VjxIEyyGCJfwWZmlHjhwZMWLEQLJkyVQeGYVrwoQJyk00cP78ecybNw+rV6/G3bt39VbgyZMnOHHiBB4/fqyG9tetW4dHjx7pvYCnpyfOnDmDqVOnYvbs2bh27Zre4wVFkxYdz33kyBG9VbBVRLAEo8maNStChQqFp0+fqv2FCxeiQoUKuHz5MrZv346SJUvi8OHDqo9/GzVqhCZNmuD69etYtGgRcufOjdevX6s42dixY9G4cWM1E+D27dsoVqyYEi7CY8qVK4dRo0apc48cOVK5qJ8/f1b9gu0hgiUYTbhw4ZTFdfPmTVy9ehV9+vTBjh07MGbMGGVF0Y1s1aoVXF1d1fH37t1T7aNHj8aaNWvUFCVaVLSutmzZgmHDhmHw4MEYMWIEpk2bhjt37qi+IUOGIEGCBNi8ebM694YNG5RQrly5Up1XsD1EsIQAQ/FgbCtWrFhq9JBWEDeKGV1AgyWULVs2JEyYUD3mc/Lly4dz584hdOjQKFKkCNq0aYOBAwfi5MmTKF26NIYPH66C/nv27EG1atVw5coVdV7+/eeff5RbKdgmIliC0Xz8+FHFptKkSYOHDx+qOBMtILp33OjSVaxYEV+/flXHR4kSRf31DcWrX79+Ku5Fi6p9+/ZqNHL9+vWqqsXz58+xYMGC7+flRreRAijYJiJYglEw7kS3Lm7cuEiRIoVy72hROTk5fd8YkK9SpQpixoypP8tvKFLbtm1D2rRplYV19OhRtGvXTs29Y1/s2LHRoUMHH+du1qyZOrdgm4hgCb+FlhRjShy9o6B07NhRBb8Za+LE3hIlSqiA+dKlS1XM6u3bt6qUyuTJk5Xo/A6KHwPqnBBOa4y5XbS6wocPj4gRIyqLq3v37mrUkccyFlajRg3lGgq2iQiW4CeML9HCYXkUJowyiZTuG2NVe/fuRfbs2dVxceLEUYHzGTNmqGoUdNcMo4EUNKZFUHy8w6B9pEiRVFE7ChtTFpIkSYLkyZOrQDvdQD6Xo4sNGzZUI4W06MqWLYuhQ4eiatWq+pkEW0PKy1gIaywvQ4uHlo0Be3t7JWR+QSEzWEgUG8NxtLLYxzYD3Ge7oc3wXEIR834sX599PIZ9YcKE0XusA74XKS9jOsTCEn4JbzYKhGH7lVgRigktp7Bhw/o4jo+9CxDxLUqG53LzfSwFkK9NN9HaxEowPSJYgiBYDSJYgiBYDSJYgiBYDSJYFoZBZAacZbONTTAtMkpoIQyjhH4FloWQC2cB1KtXT0YJTYQIloVgtc5u3bqp6Sa2Bi2NT58+qdwrW6RFixYqwVYIPCJYgtlh/SsW/Ovfv7/eIggBQ2JYgtnh3ENmvsuq10JgEcESzArdQU69oZV17NgxvVUQAoYIlmBWTp06pSYrU7joFsrImRAYRLAEs8KSMAYOHTqEV69e6XuCYDwiWILZ4JD+qlWr1GPOCWTpGZY7FoSAIoIlmA1WI2Vp5HTp0iF69OjImDGjKp0sCAFF0hoEs8M6WnQNWced9d8FIaCIhSUIgtUggiUIgtUggiUIgtUggiUIgtUgQXcLwgnA2uet79kOXNmZteyZh/Wnpb9CItGiRdMfCYFFBMtCcCms9OnTq0VIBduid+/eMvHbRIhgWQhDPayiFesiVcYceqttwKKFHu7usLfBOmBzh3dCnTp1pB6WiRDBshAGweo8ZjEKl7eOZb6EwFMpvQMcHWWZL1MhQXdBEKwGESxBEKwGESxBEKwGESwrw93dDa+ePcKzh3fg+uUzPDzc9R4v3r58hpdPH+p7v4e1qZ4+uKXvGc9X7fUf37vhYzn7X8Hr5PX651j/8k27ftcvn+D6Wd+0x25fXX/6TALHN+0zum3icwoBRQTLirh4fD+618yPjpVzoFedwmjxv9To1/B/uHLqkH4E8N+utVg8oY++93ueP7qDHrUL6XvG8/bVMwxo/A/c3X6fW0aRchrRBTVzRMXT+zf11sBz++pZ1M4VE42LJUMTbWtaPCU6Vflb+0xK4vTBbfpRgePTx/foXis/7l47r7cIQYkIlpVw48JxjO5UE2XrtMGMHTfgdOAhJm28gLRZcmNiz0aaZfFFPzL44eb6BZdPHUS6rHmwc9Uck1pZUaLFxJTNFzF9x3VM23YF/WdtQbYC/8PUfs3x1fWzfpQQUhDBsgLoei2Z2B/F/q2ntoiRo6r2yNFioE6HwYgaM44mBD8qe/rm1qXT2LJ0Go7uWKO5kz+7i181Qdm/cTE2LpiImxdP6a1eeGqu0JXTh7Fj5SysmjksQJbG2SM7NfftG5r3m4LD21bhs8sH1f7tmyeunftPWTHe4Wu8fPpAPaaLd+bQdvX6ty6dwpfPLrh65ojK6zIQMXJ0RIritcWKnxhlarfWRNJVuc2EriOfs2nRJOxeOw/vXv281Nr9Gxexa/VcHNq6ArevnNVbheCGCJYV8PrFY83COoEarfrqLT8IbWePgXO3o0gFv3O7nEZ2wfA2lfHo1hXtZlyuuZQF1I1vgLEZpxGdlVA9e3gbI9tXw3qnsXovsGBsT2WtPL1/Gw5hwmFQs7JYPWuE3us/Ni+egipNuyFpmkyaqETDpZMH9B5g3ZzRSkgMuLx/h6418iqx+eD8BgOblsGmhZPw/u1rzdXtiz71imF42yr48unXMwY83N3g+c0D9vZh1P6K6UM1K7Qh3rx4irOHd6JNuYxKBA3w+oa1royHt6/i8smDGNqqIg5sXqr3CsEJESwrgIH0OAmSIGy4CHoL8OT+Tdy6fFptDHy/e/VM7/kBY14HNy/DmFXHlHXTbcJK1OsyAiPaVYO7m5s65tOHd8ictxia9p6AZn0mYciCPZg/prsSMFo+DMoPnLsDDbqOxL8NO6Hz2CXYsniqsnz8w7vXz3Hj/HGkz1lQlUkuX789lk8ZqFluHtp+aPxdrLy6RooMoTBT1DLkLIRNmsXH53SfuBLVmvdEP83d+ytHAXWcd+5cPfP9s7iuvdbCcb0QP3EqxE2cHOf/26MJ8BgMnrcL9TsPR5exS9F26FzMHNxWWXovHt9T/X1nbkKj7mPQov9UDJizHfNGdlXBdiF4IYJlBfDm/vL5E75p/zOwYupgjNSEhxsD38unDdZ7fnD+2B6ky5YX0WPHV/u8+fOU+BefNSF6ookcCR8xCjLlKqIek3iJUyBl+uy4rd38ESJFQc/JaxE5anTlUh3YtFTdxO7uX9WInH9YqVk3FKuYcROq2NVf2fLjoWbtOb95qfrz/a+KajeIA12/cnXaqcc3L55E7uIVES6C14rRoUOHRsmqjdVjAzzP6I61vn8Ws4a0Uy5gtwnLYadZnxeP70POImURO0FSdTw/g9zFK2ifwQdlxV05fUT7MUiGRCnSqX6SOOVfmjWYUbmJQvBCBMsKiBIjNj68e63iMgY6jlqI2XvuqK1ElYYcff8Julcx4ybS97wIGy48IkeLieeaZUE4vy9S1BjqsYE4iZLBRbO83Ny+KnewVZn0mou0TLP0nsL59Qv9qD9Dd/PU/q14rglDv0b/U9v0ga2UZbVs6kB1TLjwEZE8XRbNXV2pzn/m0A4ULFdTT1n4jHhJUqjjDDDu5Z2o2mczffv175/F2FXH0WbIbMRJmEz1u3xwRuz4idVj70TUrLgXT+7j1dMH6vPwTihtCx8xsnquELwQwbICEiRNhfhJUmL1zOF6i/+glcC4lHcYdGdsKGGyNGqfIki3zTtvXzxVVtmLR/dw+sBWjF97Gi00l/LfRp2RKXdR/ag/w3gRBbHX1HVo3nfy963lwOnYt36hSocIbWeHig064uiOVep4ilcczRqys7dH6kw5cXL/Fh9rGZ7Yu0l/5D9oOV09c1RZqQYoVPxcEmt9abPmUW4vg/kGqP0vnzxAXF30hOCDCJYVYO8QBi0HTMO+jYsxvlu97wFpjqTRpTl3dLdy33yTs3BZNUJ4ZMdqvH/7Sm2rZgxHxlyFlQASxnE2zp+guVYv1GPGk+5dv4C8JSurtrCaBcRRSiasPn90F2vnjFLP8w/bl89ErmIVlGh43wqVrYnoseJj/8Yl6ji6YHQL5wzrqIliJ+W2EaZwXDpxAEsn9Vfvk8FxYwWreKX6eKa5mxwF/ah9Zu80C3HZ5IHIkrcEEmiinSZLbs3CjI6NCyYoK/a9tjHGRleTfULwQgTLSkiVMSd6TFrlFQRvWgYd/s2G3nWLYsGYbqr6A4PihCkPBhcoVrxEyrrhKFufBiXQq24RfProjPbDnRAqNP/pQyF15lxIlDIdBjUrp0bndq1xwoilhzSXKJIqg8PcKT6vU+Wcyj0sXauFJnapYG/voFlBDoivWX8GgfEORZVbgdLV9ZYf8HnFK9dXcTFC96tC/Q5Iqb3e30XKqzZCS4t5VR/fv8WaWSM0S8sDTftMVLEsnoPXoF4/9M+vb4Dxr/5ztmHLkqnoWacI+tQvrnLWekxarfo5kNF59GKc1VzRLtXyqMTc+zcvY6DTDoQJG04dEzdRcnWNQtAj5WUshKnKyzAu5P71q/rLG9chTFh18xqg68PgPAPOBgzPYXuYMOGUG0YYJ6LlRAuONzGfGyZceO28Xv2EMSNOeyEO2g3M83KEkK9Lq4ije3y+b+jGeWguH5/jF3wtCpDhubxGPsfB27k46sfgf6nqzfQW5nTtwlzNEpuy5ZK6fj7Pr9f3Dd8nr4ci7RA2rI/3SOieummfEbWXIuYl6Hz/31Qf329AkPIypkUsLCuDghE2fATlAtJ68C5WhGLkXayI4TkMcBvEivCm5I1ICylM2PDqfL5vZAbI2a5eSz+v4ebl834lFkpMfyFWhNfh/bk8t3exIrwWjoZePLFfzZ98dOcaZg9ph1I1mqp+Xr9/xIrQGqN7y8/B93skPA+tSr5Pg1gRvseAipVgekSwhGBLir+yotOYJVg9cwT6Ny6FCT0aaK5kQ5Sv114/QrA1RLCEYE3GvwupTP6pWy5jzMpjKmNesF1EsARBsBok6G4hDEF3jtAVKFNDbxVCOjWzR4Gjo6ME3U2ECJaFMAgWg7oSxLUdmNtVr149ESwTIYJlIVxcXNCjRw+8evVKb7EdPDw81PuPEuXn5FZboGXLlihUKOCFEoUfiGAJZufRo0eYPXs2Bg70mj8oCAFFgu6C2Vm5ciWWLl2KDx+8CvcJQkARwRLMCt3B+fPn4+HDhzh69KjeKggBQwRLMCvHjx/HtWvX1LSbefPmqb+CEFBEsASz4n107ODBgzY56CCYDhEswWy8ffsWq1atUo85J+/NmzfYunWr2heEgCCCJZiNJ0+eIHXq1MiUKROiR4+OzJkzqzZBCCiS1iCYHeafLVmyBBcuXFDCJQgBRSwsQRCsBhEsQRCsBhEsQRCsBhEsQRCsBgm6C0bBeYHGMnz4cKxfvx47d+5E1KhR9Vb/wSB9xIgR9T3B1hHBEvzNsGHDAjSBmQs5EL9W1/kTKVKkwMmTJxEpktfqz4JtI4Il+Ju2bdtirtM81O001M+FHEzNsV3r8PbJbZw9e1bSIQSFCJbgJ5y0vH//fmTMmBFx4sRR1hEFa/7CRVh+6t1Pq/WYg9lD2+P07tU+BEv7vqr5iOHC/XpFHiHkIoJlhVBMrl69il27duHy5ct4+vTpd7fLVFAUKBT29vYoVqwYGjdurJI/l69cFSSC9fHjR2zfvh0LFy5E8+bNkTZtWv0o0+Hg4KCKDCZKlAhhwvhv+TDBsohgWRnXr19Hly5dcODAAbi6uiJevHhGB7L9C8s606Lh1JqGDRvi3LlzWLJsuUUF6/j25arE8IIFC/Dy5UvVbudtbUVTwvNStGLHjo369esrYYwVK5beKwQHRLCsCI60NWrUSN1YrVq1QoMGDRA/fny1aKmpcXd3x6xZs5R19ddff6kbOahcwlOnTilxnjlz5vfPgMF4U0Mr7ubNm8pyPXHiBBIkSIBFixahYMGC+hFCUCOCZSUcOXIEJUuWRNKkSVXFg+TJk+s9loOCNWeuE8rXa2cWkfTN+f/24vPbpz5iWHSHv3z5YtZUB7rDtGD5g0ARo0iKaAUPRLCsAGdnZ+TMmVPdrKwpxRhLUDBx4kQMHjxY3/OJm5ubsoJoiYUN6/9VgVg2mXEyPscvEUyXLh127NgRJLlYdIn/+ecfvHv3TqVWJEyYUO8RggoRLCtgypQp6NatG1avXo0yZcrorUEDxdM7rMBAt+nMmTN49uyZKtiXN29evff3UIBpxZw/fx5p0qTB//73PxXc9x6jolBR0IIKvi9atvzcGfAPSC6ZYDpEsII5jCXlzp1bPWZcxVwB54BAq4pxrs6dOys3qmPHjhg5cqTe6z9Y671w4cIqg54jf3R3EydOrPcGDxh8X7ZsGW7duqVSPISgQwQrmMOUhWzZsqFmzZqYMGGC3howKDAcaTNFCgTdJGa+r127FnHjxkWECBGwefPmn9zBaNGi+XDn+Prad07f82LdunVK6HhOZrRzKk/x4sVNEiejwHMklVBUDx8+bPT0IqaOjBkzBu3atVP/FsZCQRZ30jSIYAVz+Kv+999/o2vXrujVq5feGjBatGiBFStW6HuBg5YfY1aEOUsUA79iVxkyZFAiQZiSwZvX8DwDFFCejxvPQ6FiYqgp3C+eg++Zbt3z58+RPXv27+kRloJu7vTp0/U9ITCIYAVzuOJMrly5MG7cODRp0kRvDRglSpTAifNXkLqEI0IF0rX8pgkLCfUbK+j+0U0I+9X5u0XD9IR8+fIhReGqiBQ3iWrzC08PD3XewArW5zfPcXPPUszW3FbmVRms1QoVKqBPnz76Uf6D1ikHFIyFbq6jo6MsVW8iRLCCOQbBGj9+vPqlDgwUrEuP3qLSjJOwc/D/SF5A2dW/KlyuHfpJsMqO2YWEOUqoNnPy8vpprG+ZC7NmzfQhWHXr1g20e+1fKHK1a9cWwTIR5k+mEQRBMBE2JVgckmcuEaeZ9OzZE7dv39Z7BEGwBmzGJaRYMfBKE52xICYCLl++XK2bxxEpc8ORMScnJ7x48UJv8R9ceJTuRKlSpYweoTK8V86NI+IS/nAJ6WJbAg5IiEtoOmxGsChMXG6KuUwxY8ZUo1EVK1ZUk1v5ZeIin2w3DKVz5IpiwWH5gARbfcN8I67RxzpSoY0IeDMDwcPdDXb29kYFoXn9bl9dMXr0aLRv3161UbBOXbqB9BVaIpSd+ZMxb+1ZCodPL38SrLSlGyFKgpSqzZy4vHqMKxun/xR059QeVmWwBEym5eRtESzTYDOCxYmzzKieNm2a3gL07t1bTXZdvHgxatWqpVYqZhlfZlYze5vVNWmJmaJ4HKd5pEqVCu2HO6FAmZp6q3/Q/nn4L6S0yv+C9eTeDXSplhuDBw1Ep06dVBtvWiZAWhJWejh9+rR6fOXKFZUE6zutwZwwD4szBMqWLatel5/F3bt39V7/wzmFzCcLyMhly5YtUb58eX1PCAw2I1iGZEnDF46/fHQFmZ1Nt4n7/PVt1qwZmjZtqm4sug3Vq1dXxwcWg2B1HrMYhcs76q3m4/Hd62hXIYsPwaJVSevC2MRR3uCc88eVm40lfPjwPhJAKRrMtzKWpUuXquRZY5NJDfMUvWPs+yejRo1SlpIhCdUYApueIfzAZoLu/NJw45eVlhbjWczQ5k1A+EWkVUVLrGjRoirJ0lRiFVzgzc6MdFoKxmy0Opn4GJDn+hYYiodfx/1uc3FxQb9+/ZRo+tX/u82vZFbDd8G/2+fPn9UUpNmzZ/vZ/6dNMB02lYfFOBWnfbByJovgcY4Yv9QGGBjnJFdWROCkV5YHNhXBwcJi8iNvemOgRcTYFy3QS5cu+SkAv4MiZyhnzB+L9+/fq0nPxsDpP61bt1YTwGkRGwMFk3FIwtenW/rkyRO17184NYfxT9bH4g+asXCmguEahMBhM4L16dMn/Pvvv+oLPHXqVFUAzvevH2Md/GIWKVJEJWzSsuANZwoMgtV60Ezk/6eq3mo+nty/hZ6OhXwIFmN2xsawKC6c0kJ3ksUCjZ18nSVLFjVXkNy5c0fFcmixGANHeA3WlbHxRP57s8oCg/2ckkO339iR2sBCa33SpEn6nhAYbEawGFindbVv3z4/Z9zTeuDNxFIuFCxaV3Xq1Pll/Sdj4SghBSt8xMhwCGv+BRQ4veWD8xuMHDHiu1VCS+nixYvKijRGeAxxL8ajjIFF8ChOvkcJmaJB8fMvFEsGvSNHjmyUi/X69Ws1IZvunPdRwswFSqNyk676Uf6D7z8g7l2HSjlQR6bmmAybECx+2ZgsytQG3xZTuXLlMGPGDFSqVEmlOMybN0/dzNu2bVOCxeJxLJ4XWBiH4ahjQH7d+RzmUhl7w9B9o3VlWLCBgsWR0KNHjxrt2gWEGjVqqEqpvgWLJYh5LeaGo5Oc1kQ3zrtgFShfF016WWZqTqX0DnB0lDwsU2EzFhZjML6LzxGOIrH+EkfCWHbY+2opjx8/Vr/uQVmfia9P4WTA13u8LSCIYIlgWTs2M0rIUUBaGr63lClTKpHiY99LO7GGUVAXk7t3756y8mjxCYKtYzOCZa0wYM2AM+MwtLaEwOP57Rs8PNwtsgmmxabSGqwN7d9GzXvbsGGDclfpygUm655uGCd8d+/e3SJ10unG0q327RJ26NBBLR1mbu7fv68GWnwH3b/ZhUXcRMn0o8zL9XPH1L+huISmQQQrmGPKAn7M1GbqBgchTIHhPL8bDGDFUQoVYQ5U/vz51ajjrwjoaNyvoDAzS54jwHxdzmIISJUOjnYGtAoqBTqkJSEHFSJYwRzGsHLkyKESXVkSJzAwF42bqQSLo5dc6YZpIkyV4Np9vFbv8CZnOgKhS8u67d4TRzkIsH//fhWnY8pJtWrVMGTIEL038DAPiytjGyxKvndjpwYxeZYlqln0z3fmvn8wxeR5wQsRrGAOc4mYfMnpQsFxmalFixYpq4ViRAvOMH3Fv9DaKVSokErq5FJftMYMmfHBBZYhatOmjXIpRXyCFgm6B3NY8oZxF04XYkwrqKEwed9Y64m5bMxdY3IuUzBoRfk+zvdGK4tLejFJl1YWy73MnTv3+4IWhs1U1mBA4XQuzn7glKIbN27orUJQIRaWFcAbu2rVqsotYfJpULFy5Uo/1x1kfIdiylw3/uW8uT+lgzCRllN1CCeh0ypj4q5v64wVIpjYa4m8Mb/gNC4m3zLLn7MgKMhC0CGCZQVw0nKVKlVUrIdLVpUuXVrvsSxt27bF7DlzkL1AKU1Y/DbOPT098PH9W0SOGvO3rqGr62dVmDBCxF8X0ntw6zLsPF1x9uxZk9QkMxYWcGSdtHPnzqkYG/PyKK5C0CGCZSUwllWsWDE1iZpWVqNGjdSio5aEgjV/4SIsP/UOdvbmj+XMHtoep3evDhLB4hqKHJWlWLFqKyt7BLf4oS0igmVFMDDNm2j79u2q2gTjRyw0yPiPJW6msWPHYtuOnRYTrFlD2uP49mVYs2aNRUoac4I1S8+wnA0nTfMzpRvIKUYBGR0UTI8IlpVB95DZ78zLYiFCBqaNLfkSUPharDRhKcGa0L0+9m1YZLGROb4/pjxwgjxFiuV4GIsTyyr4IIJlpfDmYp0qLmXPYLclYCWLQ0eOWkywZgxsjSNblqjBBlPVJfsdHJFlBj7TKxhkF6EKfohgCf6GMSynefPRc/Iao1b+CSjbls3Aw6sngyzoLgQ/RLAEf9O3b1/ligaEgE65YayOJWostSyXELwRwRL8DZMnuSyasXA6EEfbOPHZWGLEiIFkyZKJeyYoRLAEs7Nnzx5MnjxZDRaI8AiBQcZqBbMzf/58VRqHOWSCEBhEsASzQjdy48aNan4hs8UFITCIYAlmhUmYhmW9FixYoPLIBCGgiGAJZoO5Yiw3Y4BLjAWkeJ4gGBDBEswGq6Vy5RpWWmC2OgPurJ8lCAFFBEswG0mTJlUWVsWKFVWdq3bt2qlJ24IQUESwBLPBdRS5AIOhJIujo6NaVk0QAooIliAIVoMIliAIVoMIlmB26BpyYwlkQQgMIliCIFgNMpfQQnART1avZJ1wW+Pw4cO4dOmSWgbMEnWtghssBsiVj4TAI4JlIR4+fIjUqVMjbPgIsHcImhVgggpPDw+4u39FmLDh9Rbb4cO712jYsCFmzpyptwiBQQTLQnDib6pUqdB26BwUKG1by5azFhY3W6yLXuvv6Kjj6Ig5c+boLUJgEMGyEAbB6jxmMQqXd9RbhZBOpfQOcHSsLYJlIiToLgiC1SCCJQiC1SCCJQiC1SCCFUJ48fg+VkwfglEda2L1zOF48+KJ3vNn3N3csHvtPIxsXx3zRnXFwS3L4Pb1i977M/euX8CuNU749PG93vIzx3avx551C1SwPTC8e/0CO1bO9rGd2LsRzx7e0Y8IPBzJG9etHlzev9NbhOCKCFYI4O3Lp2hXMQuePbiDbPn/hzcvn6FrjXza/p9rT3l4uGNa/+bYv3EJsuQrgUQp/sKC0T2weEJf/YifuXvtPKb0boIjO1brLT55/fwxpvRpioVjeuCbp6feGjCea8K0ZGJfPLl3U4nU0/u3sHPVXO395dWusY8miIE7P/Fwd8fZwzvw9TciLQQPRLBCALOHdkCeEv+i3bC5KFm1EZr2noBMuYtg+4pZ+hG/5v71i7jw3170mLQK/9Ropp7fY8oa7Fo9F19df30Dh7azx4Z54+D6+ZPe8oOrp4/gy6ePCGWiNIYIkaLCsf0g1O88HA26jkSfaevRceQCZW39zsoTQh4iWCGA7AX/QY2Wfb6vSMO/TFB99/q52p+sWUO7Vjupx+TmxZMY0a4qPjq/QdSYcdBWE7pIUX4sVBojVjzN8vLAZ5cPesvPJEiaSnuNiDh/bI/e4oXrl09YOrk/qjTtrl3Hj68XrbKJvRqh+f/SoP2/2bBofG8maKmk0mVTBmHb8hn6kcCrZw8xqFlZPLp9VW/xhfb+UmfKBTtNNOnOErrEE3s2VOfvVbcI/tu51of1xfcya2h7tC6THn0blMR6TWy1C/DqFKwGEawQQIkqDRFfExB3t694++oZDm9bhfNH9+DfRp1Vf+Wm3bB86iA8unNNcx+fYfqAlsiStzgiRY2BmHETqseMNX3QBOzO1XNYpLlahcrWRNQYsdXz/cI+TFjNImuOLYun+BCG80d3I1yEiMiYq7DeAhUbGtqyIjLmLIShC/ag2/jlOH1wm3odriCdp0RFrJk1ArevnFEuak/HwvgrRwEkSvmXfgbffFOiFi5CJJU9//LJA/RrWFJzZ9Op89ds3Q9LJvXHpoWT1NEU0TGdHeH6yQW9p29AnY6DcWjLckwf2DrQLqtgWUSwQhD3b17CwCZlMHd4J03EGiB+Eq9ieQmSpkaF+u0xvX9LzBzcRhOTIvinZgvVZ4Au3LR+LTCmUy2c2r/FX9n4OQuX1l7zMh7e8rKEKFxHd6xF4fJ1fEw/Ymyo1aAZKF65AWLFT6xdVypUqNdevQ5Jni4LGnUfi9EdamLW4HZKRKs176n6CAcQFo7tqQYEnEZ0wbDWldUAQfFK9RE+YiTsWTdfCTatOp4/c55i6DhqIVbOGKYsuLOHd+LJvRto1ney+izSZsmDgXO3Y++6BeozE6wHEawQRMr02TFh/RltO43LJw9h4/wJqp0uYtk6bRAmXHhcP3cMtdoM+O4+GggfMTK6T1yJaduuqpudbuSfRhqjx46P0jWbK0uJVg/dsgvH96Jg2RpeB+hEixkXMeIk0MSyLQY0KY0+DUooMXH94rWaDmEMLmnaTDi5bzP6ztikt3oRWbMEU6TPiuR/ZUWKDNlQxrG1dsxGVGnWQ/VfO/sf0mXzuap0vMQp4PrZRQ0A0GrM+HdhhNXevwFalyn+yuavgQkh+CCCZeXQDZwzrCO+aDengagx4qBU9aY4unONWrmGPLl7A08f3ELEKNFw5vB21UaYIrBvg8+FIXIUKq3m/T3WnvMnStdqiXNHdmkWmovm1o1EkfKOiKEJmXcYv+rX6H/K9eTAQNdxy5TF5537Ny/i9uUzsLO3V8F07ziEDadZfDXUubllzVcCCZOn/T43MXykyMqS8o6b6xfl5oa2C62Oo1voG/aHCW971SOsGREsK8fO3kHlTW1eNFlv8eK4JkQx4yVSltT7t68wqkMNVG7cVYkFRxVfPL6njvvg/Bbblk3HV9cf1o7zm5d4++o5osT4c8G9KNFj4a/s+VQaxPULx/E/TSh9c/H4PqTPUUBZUbS0oseOp+JpBjgaOWdYJ5Sr21a5aqtnjcCVM0f03j+TIWchHNu9Tt/z4urZo8pqpBWYrcD/lKgyfmeAn8mdq2eRSBM+wXoQwbJyKEi9pq5TgrFsykCVGzVjUGucPrAV1Vv0Vv1MJI2TMCn+V60JkqbJhLKaSzW0dSVlYeQvVZVn0QStJg5tXYm96xeqUTa6eklSZfB6kT/g2G6QCnDTDePmm3iJU+LSiQNKNPiXAXCOVBJPTw8Vc6O4lKndCgmSpUGbIbMxvls9NQjgH/h+eJ7+jf/BuaO7sWXJVEzp00S5lqFD2yFVhhzImr8EJvZqiENbVmDf+kVoVzGrZuV10D6XZPpZBGvArm/fvgP0x4IZcXZ2xqRJk5Dvf5WRLG1mvdU0xIqXGMUrNVCWDEfaIkaOplyvJKnS4/XzRyrpsna7gWpUjaTMkB1fXD5orlQUxE6QBAXL1sSb549xct8mfHj3BqVqNFc3s+84lwG20+1LlTGH2o+lWXKRo8VEwdLVlVVH+NRImvuZNmseFRCnINESfHz3uubeVVNB90jadTJuxWTQGq36atcdVT03ccq/EDGS9lg7R2ztvdGNTZM51y/L0/B66JrSUjuybZWyFhv3GI/UmXKqfopWjsKl8emDs2a5Hcb7d69UgJ5usxehEEZzO//Klhf2DmH0NtOwYupgZM6cCRUqVNBbhMAg5WUshJSXsU2kvIxpEZdQEASrQQRLEASrQQRLEASrQQRLEASrQYLuFsIQdK/cuAsy5i6qtwohnSEtyqNOnToSdDcRIlgW4unTp8iUKZNan9AWYc7Xr9IkQjotWrTAmDFj9D0hMIhgWQiWa7l8+TI+ffp5ikhI5/Pnz7hw4QJy586tt9gW6dKlQ7Ro0fQ9ITCIYAlm58CBAxg1ahQ2bWLmuYRNhYAj3x7B7MyfPx/Hjx/HvXte8xcFIaCIYAlm5cOHD1i3bh3ev3+PLVu86l8JQkARwRLMypo1a77H7RYvXoyvX7+qx4IQEESwBLPBkcHZs3/Utrpy5Qpu3bql7wmC8YhgCWbj2rVrOHPmDMKFCwcHBwcVcF+yZIneKwjGI4IlmI3EiRNjwYIFqFWrlhrWHzp0KOrXr6/3CoLxiGAJZiNSpEioXr06okePrqwrR0dHpEmTRu8VBOMRwRIEwWoQwRIEwWoQwRIEwWoQwRIEwWqQuYSCv+EE5kWLfK5h6B8OHTqkUhzq1q2rUhyMIUOGDOp5dnZ2eotgy4hgCf6mQ4cOmD59ulrJ2Ri4BBcXfA0T9sfKy/7hk8t7xIoRHWfPnpVqB4JCBEvwE2apsySOvb293gK0bdsW8xcsxNx99xHaW/uf4Lm+aecy5jlk4ZieuHBokxIspkYIggiWlePi4oK3b98qUTAl7u7uGDJkiKphVbFiRcSNG9dLsBYuwvJT79SK0+Zm9tD2OL17tQ/BOnfuHOLHj6+uR7A9RLCskPv37yvXjBOLHz16ZHKxMqAsI20LHz48KleujI8fP2L7zl0WF6wdO3Zg165dmDt3Lq5fv47//e9/iBEjhn6U6WCiK7PzCxQogL///tuHdSkED0SwrAhaPSyEN3r0aCUkWbNmVVvs2LFNXn7Y09MTy5cvVzcxa5IzY33w4MEWt7COb1+OPn36qBI1rKnF6qW8JnME4fmZavcDXF1dkTx5cgwYMABVqlQR4QpGiGBZCbyJmjZtilWrVuHff//FoEGDkDp1ar3X9FCwHj58iESJEn0XB0MMa+au25pgmf8mXjS+Ny4d3vLdJbxz5w42b96MEiVKIH369PpRpoNiyCKDfL1x48apkc3atWtj/PjxiBgxon6UEJSIYFkB/OXv1KmTcgP79euHLl26IEyYMHqv5TCMEkaNEUf75uiNZuTzxw+IFTNoRglZcHDixIkYOXKkmgM5bdo0Sa0IBohgWQEs0VKkSBEV/Ga54aC6cS5duqSqL/jm9evXuHHjBp48eYK0adMiY8aMes/v4QpCW7duVblZKVOmRLJkyRA2bFi91wuuNESXNChqwXOUtH///sraWrhwIapWrar3CEGFCJYV0KRJExVg56o7CRIk0FuDB2vXrkXz5s3VaGXSpElx+PBhxIwZU+/9Myzw16ZNGyVUDHZv3LgxWMWMnJ2dkTdvXiWqp06dkkU0ghj59IM5rIm+Z88eddPEixdPbw0ecLRyypQp6qamNTJ58mSjxIrUq1dPjfrR2vrvv/+U60UXOLgQNWpUtGvXTv1Y0DUVghaxsII5DHxnz54drVq1wsCBA/XWgMEbjiNtpuDFixeYMGGCsqyYChA5cmQ0a9bsp9FKunolS5ZUj3ms9xrvBpiaQUuNi83yGFpaHJU0BYz1VahQAbFixVKi2Lp1a+W+GgPTOVjemSOHHJE1lvbt24s7aSJEsII5zDvKlSuXSmWgIASGsmXLYrdmrdmHC/yI1zdPD02cNAP9N+kUHq6fET9eXNy9e1ftUzBpKYZ2CIdQv4nDffNwR6jQmlsYyMD+N09PuH9xUXE/jvZRELNly6bcT8bLjIHJuUynYKlnYzh27JiaCylL1ZsGEaxgDofWKVgcWm/cuLHeGjCYDnDh7nOUHLwOdvaBG2V0//pZnSNU6F8Lz+GJrfH1/lllQRHGgPLly4eiPRcgbob8qs0v3L58hH3Y8JoWBm5w4c3di9jVrzJmzZqlSjMbBIsCQuvQElDgKJYiWKZBYlg2RmiHMIiSIAWiJEwZqC1G8oyImjiNn32GzSF8JP1VfRIhZgI/jzdsMVNmQdREvz+3f7aIsRNrr2aB/AvBYohgCYJgNdiUYHHVFmZMe9+YCCkIgnVgMzEsDrszhsPRmlKlSumtUKNHlsiiZnIlkz85umYMvG6mNnACsu+kyj/BEbKZM2eiTJkyap/v/9Kjt6g0/STswhh3roCwq19VuFw/9FMMq+yYXUiYo4RqMycvr5/C+pa5MWvWTB8xLI5acuTOEhQsWFBlyksMyzTYjGAxV4jD5evXr1dD7d5xc3NTw+0cns+f3ysYzKF3ZnWzSoEpSpk8ePAAqVKlQposuREnQRK91X98cH6LSFGi/ZQy8Ds+uXzAucM7MWzYMDWth1CoDxw6goixEloktPP57QvEjBpJpWaQ06dPK8EKHz0e7MIaV3k0IHi6fYXLq8dKLJjv9fLlS1WF4fnz5/oR/oe5YQGdYM7RXU7zEQKPzQgWp41QjJiHw+H1CBEiqCkfhQsXVv1Tp05VN/fJkycRJ04clV3OCccsacJjA4tBsDqPWYzC5R31VvPx+O51tKuQBYMHDfwuWKx4wHwnY+HnwBvW2PLGJEeOHGoOIqGV2bdvX2UxGgvTCujCGwutTM6/ZBY+4b89hctYaB1myZLF6LQGQqsuIPlbws/YjGBxyghdI4oULa2DBw9i06ZNmDFjBsqXL6/KitBtoPvCYW/Guy5evIgoUaLoZwgcwUGwAsr+/ftVekWLFi30FsvCsjpMDeAy9wERDFPAMjMtW7ZUbrUQdNhM0J11ozi9gtNH+OWnUNWoUUNNbCX8JaaVxRImtAiWLVtmMrGydpjH5OTkpOJpQQEnXXOSNIUzKOAUJE6P4ucgBC02nTi6YcMGNfHWEGNhSZEUKVKoWlCc01azZk3VbgqCg4VFK4k3vzFz9RjL69q1q4oBct6gsQMUdMWY+EpYb4o3Pv8aAy1hFhPkoAVrghkDf4j4PM4JpBXNz4LTbIyB752fGwc9cubMqbf6H/4AcnqQEHhsRrB69OihhIluhQH+YhoKtRGWb+FoHGNdLCty/vx5FYg3BQbBKlenLdLnKKC3mo83L55g3uhuGDpk8HfBouvLcsOWhAUAabUS1mPn1BxLWmoMlHNqTq1atb6PEn71+Gb0yj8u798hbPgIsHcwbobAozvXVKiBVSmEwGMzgrVz5040bNhQWQkcqaJIMSbBjZU0OUrYvXt35XbwJqtWrRpevXqlXBGKWGDhzcI6UZyAayyBGaGim9ugQQP1mPEXDj7MmzfPqFgQLRPGkYwdfOjZs6dyw32nNdB6NVhd/uXNmzdG13G/evWqGh30PTWnQPm6aNLLMlNzKqV3gKOjTM0xFTYjWPxVZ3lhxq5oaSVJkkQNN/OXl6NXHBVksJ1pDIRiRfejW7duyioILHQzOZGZM/+NhVZR8eLFja4TxUJ/LIBnECcKFkfbjh49anROV0BgjPDIkSM/CRYXlLBE8JppFBRG5qKJYIUMbDqGZQ0wBYCCyVrmxlYY8I0IlgiWtSNzCYM5jPvcvn1bYiCCoCGCFYxh7IpCRXd29erVKo4kBB7nNy9x58pZi2zGjMgKf0ZcwmAMh/+Zac/BAAaPmSUemJrudMNYUI6DCgEN4hvDs2fP1PJYvl1CvgdTzB74E8zQZ7ySok+XkPM4mY/3+s0bhGbxQQvg4eGu6pjJJHvTIIIVzGE5X85/43JTgc00Z/Ln4sWL9b3A8+7dOzx+/FilfrAaJ0XQtxDmyZNHTXkinMPHgQ7fU3M4IEErkv08Z4YMGUwmqBxw4MiwYQ1H5oFx7UFj4YhjunTpAnRdrFlvqvQYW0cEK5hD64Q13fkrPXz4cL01eEALkLldnObEm5mr53CupjEwKZPTpTh1iikfzJMzjNQGF5gKwjQXvk9ZmzBokRhWMIer0DD/iCvK0BIJTjA/je4Ws9+Z18a1+5hF7t+4DQWPFTEoBFx8ghYkV7UOTtDyYxIx14bkTAghaBELywro1asXJk2apFIEWDEgqGBKBCeE+4ZrCTJVgW4TBZYrU9ON/R3a9w6jRo3CgQMHVHUMxrq40Aan0HiHVQ4C6oqZAsb8DMuQMYnYEukYwq8RwbICOK2HZVq4qjKTSHlzBwUM/nMxDEvCpbVOnDjxk5BZCgbLORewaNGiyi2naygEHSJYVoLhxmHMiFNruA6gpeEUJqf5CzDIaecvYzl0Bz++f4fIUX9fu8r1y2dlNYX5TSG/DQsm4O75I6qGVUBqYQWWffv2qQnwFE1O2WKybVBZeoIXIlhWAoWAsZQRI0Yot5DuVKFChSwaBKZgzV+4CMtPvYOdvfnrUs0e2h6nd6+2uGDR9eV8R7qorDbBooe+q9QKQYMIlpXBIPWAAQPUyBXjO3QVuYS9JX75Gfi/c+++xQRr+oCWOLRpsZrnGZBqp8bCCdY3b95U+WLM4aIbyM/b2EnXgvkQwbJCeGOxlhfrRHFCte+l380Fc6TcPb9ZTLAm9miIfRsWKsGwhCBzcjkHAGjBMkXjTwMHguURwbJy6CoGpGRNQGBdrcVLl1nUJTy5cyX27t1rkZWNaMUxAVYIvohgCf6GMaxZs2cjWZpM2jfH/BbP6+ePESmcQ5AF3YXghwiW4G+4RBqD/cZCK5AxoYDEodKnT68C4Cx1LAgiWIJRBKS8MecIstqEsdN2CGNXoUPLhAzBC/kmCEbBNApjty1btqjcMZbH8av/d5uIleAd+TYIZoXuIKtEMF3gwoULeqsgBAwRLMGscO4hSxV//fpV5TRRwAQhoIhgCWaFrqABuobM5RKEgCKCJZgNJrR6XweSi0CwlIwgBBQRLMFssEYWg+acPMySyLFixVLlWgQhoEhag2BWWKSvT58+KvB+6NAhk5Y/FmwPsbAEs+J91WzO1ROxEgKDCJYgCFaDCJZgdjglh1tQVQ0VQg4iWILZMWStc8ktQQgMEnS3IIb192wNFhycP3++KozHkUJbQ4TadIhgWYiXL1+q6qAsvmdrUKQp1rZ64w4ZMkTV4xcCjwiWheDKN6lSpUL6nAUQL1EKvdU2+PbNE25uXxEmjPnLHAc39m1YhLp162LOnDl6ixAYRLAshEGwOo9ZjMLlHfVWIaRTKb0DHB1ri2CZCAm6C4JgNYhgCYJgNYhgCYJgNYhghTA+u3zQHxnPV9cvNlmvysPdDW9ePlUjmULwRgQrhLB9xUzUzhUTtXJGh6P2d+eqOfjmzxvw1qVTaF8xK6pnjYRKGRzQr9H/8PrZI733Zw5uWY7WZTPi7rVzesvPDGtTGT1qF9REIHB5Z3eunkPz/6XWtjT6lhrdaubDiulD1HL3puDDuzfo8G92OL95obcIwRURrBDA0R1rsN5pHAbM2Yb1V93RbeJKLBjTQwnLn3D58A6jO9ZC6VotsfaSK+Yfeox0WfNiQNMyKh3BL2iRPLx1GZsXTdFbfHL78mmcObgNTx/cAgJpsLlpVl+oUKG197YVQxbsRq8p61CnwxDcungKg5uXg7vbV/3IwPGr9yoEL0SwQgD7Ni5CnY5DkCZzLrWfJW9xlKndClfPHlX7zx/d8+Eq8iZ/ev+WZqF8wo0LJxEtVlwUr1Qfoe3sEC1mXPzbqDNePL6H929f68/4mXARIuLiif3aMa/0Fi/oUjL3KH3Ogggd2l5v9cryf/bwDs4e3oGrZ47gyycX1c7jXz19iI/Ob9U+8XB3V2LnXYxixk2E2PGTIGmajMicpxia95uMBzcv4dPH9/oRwFvNrbty+hAe3r7qo53wdd68eIoLx/bi0d3r+PLZ6/UF60IEKwTQadQi5C5WQd/zEqTH2k2pFjzVWDtnFEZ3qgW3r65qf9aQ9pg+sBU83NyQQROWgXO3wyHsj6ROCl2kKNG17derLcdNlAIp02fDpoWTtL0fZpTzm5c4dWAbCpWrrbd4WS+rZw7DiLZVsVcTs5UzhqF77QJ4dOea6j+0bQWGta6krClCwRvQpAw8fzONyc6OpWp+fH2XTRmInnUKY/288ZjSpykGadbXyycPVB9d4+3LZ2guagEsnzoYk3o2Qo9aBTTx3Kn6BetBBCsEED5iZDiECYu7185jar/maF8xG9zdv6Jg2Rqqv1GPMfiqWVPbl8/E5VOHcHL/ZnSfuAoRIkdFGE2owkWIpKyaheN6aUJRGhO7N0DX8ct+uxw9rbHqLftgz7r5mhD+sIT2rJmHhMnTIEHSVHqLV4yIItZj0ip0Hr0YfWdsRI5CpbFm9khVH4vuqJ2DAxaM7alZSIexZGI/dBm7BGHCedXSogB/cH6jnee12p5r1t/auaOROFV6de1XtPe0dck09J25WXMZ12LY4v3KrZ3Uu7GyrF48uY8V04ag36wtGLpwL0YtP6Kufebgtt9FXLAORLBCEJGjxUTGXEWQq1h5PLp9De/feLlrYcNF0ERrHLYsmYLxXeui3bC5iKiJlXcocCnTZ0fRf+shUcp0OHdkt97za5KlzYwo0WMpESSfP33ULKiFqNthqA/rJ1LUGEooIkWNjge3Lmuu3GVlwV0751UuOVz4iJqVuBDH92zA2C6OqNGqN1Jn+lv1kXevnqGnYyF0qZZHbX0blMCTezfVrAEK7oHNS1GiakMkTJZGHU/ri27t9bP/aa6hM/7btQ7ZC5ZCohTpvhcQzFuykorFXTy+T+0L1oEIVggiVrxEKFyuFup3Ho5ileprrl87ZWGQxCn/QuwESZUlkz5HAdXmHYpa/n+qquf31KyUrcumaS7bdb3Xb3jzl6vTFksn9VOvc+7ILhUDS5jCSzi+o/WtcxqDrjXzK+tp5fShOLlvk49RzOix4yNu4hT4+P4dCpSurrd6ESt+YkzacA7Ttl1V2/Rt19Bn+gb1HELXMn6SHxYdiRYzDkKFDg3n1y814X6piZhPa5F9/Dx+NxoqBD9EsKwc18+fVDrC43s39BYNTUgoUG9fPvsuWCumDUbYsOGRKmNOzB7aAR4e7qp90fjeat87tH7oan128Rm49ouCZarjlXbTMx60f8Mi5Cnxr+ae+pzkfPrgNhzcvAxjVh5Dz8lr0G3CChSv3FDv9QqIc0Tz2YPbqFi/Awa3qOArJyqU5oLaay7qj827BUdr7M6Vs/qeFy8e31cxsHiJkyNOwmR4qp2bwmmA56dYxdetMsE6EMGycsKGj4BsmruzfPJANTLGmMzr549UzKZw+dpq1Zprmmt0eNtKNOg2Cm0Gz8LNCydVYJv8lS0fjmxfpdw0xoo4csg0ic/auRIkTa2O+R1hNXeuVtsBWDiup3LxONroG474cYQvvCaCtKruXb+oLC4DfO25wzqi97R1qNKsuxLT1TOH+zuRs9i/9dU1M4ZHkeII4LblM5RrHDq0HXIXr6i5kDdwfO9G/T1+xppZI5RbnDR1Bv0sgjUgghUC6DBiPlw+OqNP/WJq9K13vWIqvlS+Xju4u7up4HLdjsNUDIcB+pYDp2HtnNEqGJ294D/quMEtK6CHYyHtHMWxYf44FZSP+ItRwjCapRYlWkx9D8hfqqqKM1Vp2k0F8gkrjDJdQjOOlIvHlILe2vVx9I6uKnOp2E+BXDZ5ACo27Ijk6bIq17T3tPU4tns97t+4qFxYxsl+t3hFEk10mvWdjLFd6qBPg+LqPTCptUmvCcra5Ot0HLUQiyf0UUmx7D+huaTMV2Pcj+5h1BhxlLgLwRspL2MhzF1ehjc+R+O+uHxA+EhRECNOAnWTM7DM5NCImpvHYLQB5k9xFI4Bb8M+UxIoRjHjJoC9QxjV7hdMP6CVwiC6AT6XaRCGkUXWv3L95PL9GJcPzipPiqOZ0WPHUzGlL58/agIaBR/fv0Vk7fooHAZc3r9T10cR+aS9J/ZTfH7Hu9cvtOe9VS4pRYoBee/wnHwtws+H10Jo9X3w4xpMgZSXMS0iWBZC6mHZJiJYpkVsYEEQrAYRLEEQrAYRLEEQrAYRLAvzzfObGq6XzTY2wbRI0N1CGILuTGKM7G10TQjZsJ6XrJpjOkSwLISzszPq16+PV698lmOxBWhpuLq6Inx4r8nMtka7du1QvbrP6UZCwBDBsiBcUNQwVcaWePHiBZYsWYKOHTvqLbaFvf2P/DchcIhgCWbHyckJ48aNU0vVhwtne4upCqZDgu6CWaFFScG6c+cOzpw5o7cKQsAQwRLMyuXLl3HixAm4u7tj0aJFNukSC6ZDBEswK7SuDGzbtg1v3/6o3S4IxiKCJZgNFxcXZVURTsR+9uwZ9u/fr/YFISCIYAlm48aNG4gUKZLKP4sSJQqSJk2KkydP6r2CYDwySiiYDcar3Nzc0KdPHyxbtkyNEsaOHVvqTgkBRr45gtmgGxgmTJjvAuX9sSAEBPn2CIJgNYhgCYJgNYhgCYJgNUjQXTCK9+//vPSXb/r3749Vq1bh6NGjiBbt18vf+0XEiBHVghaCQESwBH8zdepUNeJnLNp3TGW6s1rD71a/8Yv06dNj165diBAhgt4i2DIiWIK/adu2LebMmYsiFetowmNMNOGbWpkmVGjjLKUb54/B/dM7nD17FtGjSw0xQQRL+AUshXPv3j0kSpQIYcN6LYdFwZq/cBGWn3r3fTkvczJ7aHuc3r3ah2Cxthbzu8RNtE1EsKwQ3rAsBHj+/Hlcv34dz58/N/mkYgrDypUrVcypRo0aqgDd8OHDsXjpsiARLNaUunDhgprqU6VKFWTIYPoVmymCFGdm5Uu+WPBEBMvKYDG80aNHY/ny5Xj58qWK7QQkNvQnKIDv3r1TsacECRKgWrVqeP36NVauXmNRwTq5c6Uq/Dd37lzcvHlTXRcD8eYQFCa2cipR2rRp0bBhQ5QuXVpiZ8EMESwr4vjx46hXrx6ePHmCihUrqpuKN5fBZTMlFKpRo0ahSJEiKFSokHLJgsolPHTokHJPp0+fjoMHDyrxTJgwoX6U6eAI6K1bt3D69Gncv38ff//9N2bOnKkC/0LwQATLSrh69Sry58+vLABaV3ny5DG720K30PtrULDmOs1Di35TENoCMaQDm5fh5b0r32NYtK4oKpyfGCtWLP0o08LX+Pz5M1asWIFu3bopC2vz5s3IlCmTfoQQlIhgWQG8gfLly4fHjx/jwIED+Ouvv/QeyzJw4EAMHTpU37MMyZMnV5OmI0eOrLdYjnPnzqFUqVKIGjWqugbGtoSgRQTLCmClg0aNGmHKlClo3Lix3ho00GXyztOnT1WNq2PHjqnqot27d0fJkiX13t+jfffUSkJ0P7NmzaosSG4ODj/cTVZ3oGAEFUx4pevdvHlzjBkzxuSxQsE4RLCCOXTLihUrporfXbp0KVitwMJr27BhA2rVqqUeV61aFYsXLzbKVeXIX/HixdUyaNmzZ8fOnTuDlSXD91W5cmWVpc+69HTJhaBDBCuYw1FBWh8VKlTAjBkz9NaAwZvv06dPJkmBoJvKIPj48eOVRcSROwbEfSd4cpUc7xYTX585XgZ4LbQceZ6PHz+qdIWxY8cq8TIFFE9eG+FrMXhv7PQivq8uXbpgwoQJyjU3Frq14k6aBhGsYM7t27fVaBWnxHTq1ElvDRic00f30hRQsCimFAG6bBQhvwLhmTNnxurVq9VjisW///6rRMs7fC5FhCWV6R4yvYCpFKaAgjV//nw1SMHctVy5cuHRo0d6r2XgQqp0J4XAI4IVzLl27Zq6yWiBBDZ+VaJECRw7dQ7xMhdEKDOPMJKX108hkp3Hd4Fg4JoWStwMeREuqnlG+bzz9aMznl44hNmzZ6lYGeNt2bJlU2kajEkZw4cPHwIU+C9XrhwcHR1lqXoTIYIVzDG1YF169BaVpp+AXRjT5275Zle/anC5fugnwSo7ZhcS5iiu2szJy+unsb5lbsyaNdOHYNWtW1e5d5aA7nDt2rVFsEyE+X9mheCHGumywMY/v8TXsWbbhJCETQkWEw45/M5g8aZNmwJU20kQhKDDZlxCBnobNGigkgGZJvDgwQM1pM5EzJQpU+pHmQ8GljnFxNiFRJks2qNHD3XtHP43Bk7m5XMMo2TfXcIZJ2HnYAGXsH9VuFz7lUtYQrWZEy+XMJe4hCEImxGsLVu2oE2bNirPJ3Xq1GpEigHRNGnSKIuLQ+rMsTHkEHH0i4FWU1W85E3LeX9ubu5eHpkR8FoCkrDI502cOBEtW7ZU+xSsM9fvI0/L0QhtZ/65gOeXjcK3V7d/EqwcDQYiZsrMqs2cvH9yG8dmdMXsWT6D7vx35r+7JdizZ48SSBEs02AzgsW5YRs3bsSSJUv0FqB3794qqL106VL1hSbsp0CtX78egwYNUtUuY8aMqfoCAy06LijapOd45C5RUW/1HwERrGcP7mBgszIYMnjQ93QIJnbyM7AkzEFiCRxCi5bpBUxdsCRM5WBJGlrZTHLlxGZjcXV1DfAkc87BDOoZCiEFmxEsxq+IIYnxzZs3agoJXSZWJeBNxV9/JmcWLVpUzSFjHShOgDUFBsHqPGYxCpd31FvNx+O719GuQhYMHjTwu2DRYmSlBwqgMdAy+fLlixIfY2FuliE/i4mrFAve/Maye/du9W9lrHDz3ztZsmTfrWSKpffEVf8yS7PSKPgxYsTQW/wP88pkSo9psMm0BopVmTJl1C8uLQ5+ocmaNWvQunVrVU6E4sLSIqb6ogUHwQooTk5OOHPmjMpIDwo4OMJsf16DsYtYmAL+2PH1W7RooawlIeiwqVFC/rKuW7cOuXPnRs6cOVXA3SBWpFKlSioz+/Dhw2jVqlWI+1WkZUULw5iNlhWFm58bs9v9OuZ3G60q7/DfwK/jfrft27dPWYYLFizws/9Pm3cYq6TFaMxG6+7u3bsqY96v/j9tvq9BCDg25RJyisSRI0cwadIkFC5c+CdBYryKsY6MGTMiS5YsyqIwRcCdGCysDiPmo1C5Wnqr+aCF1anK3z4srNmzZ6t4nTFo3w9Vj4o3XY4cOdTcQGPgcwzTUjiBu1mzZso1NQaKBQWLlRuMDZZzsjgHHmg1c4SWSbgBiWEFBlawGDx4sL4nBAabESwWYevQoYP6tfRuVRngDcEYCY9hDIvxLNZ/ootoCihYHJ2Mmyg5IkcLfBD/T3x1/YIHNy9j+PBh3wWLo4QcqeMEY2OsR1pFtM6MrRTBUjR8ju9RQtbzMmYyMF+bPziMBRkDR4JZ4YJC7X2UMMlfOVDYyB8Nd+317b1N4vYvk3s3QZ06dWSU0ETYhGDxC8+5Y3RraFl5hyWA2dekSRM8fPgQ27dvVzfGwoULVf4TBc4UJXJZPoV1lVgX3VgMKRfGQrEYNmyYcoEJBYtWBkulmKOssm84aEGL1rdg0ZLltZgbljqmRUWX1rtgFShfF016WSYPq1J6Bzg6Sh6WqbAZC4ujgFy0wTfMs+IvPt0eWh6GX36KHIfhucCDqXJ2eE7fMZ0/wedwEQauWMNrMQZaUd5rU4lgiWBZOzYTdGfSZoECBX7a+AVmXCZv3rw+3BTe7IxjmTLBkOdkTMyYjXEfLrf133//+dn/u82YQnqCYA3INzqYw8x8WkXMD6O1JQi2jE3mYVkLDDQz1YIuVJw4cVQAOTD1zemGcW4i3RNjA9gBgTMJrly58pNLyNFXFiU0N1xpiHFDJn16dwmjxk2CjDkL6UeZl82Lp6BuXQm6mwoRrGAMLaqLFy8q15XZ+Jze4b3csLFQ/Din0pJwRPbGjRvqMVeq5tScgGSaBxS6xRxA4crVTKfg4qgUbWNhWkdA6+m3b99ejT4LgUcEK5jDhQ+Y5NqrVy9VVzww8EZlTpOpXEsukc+J1cwvo/XGwYvEiRPrvV7Ejx9f9RPtu6ZEi8moBigiTH9gjI4JonyvzFsyFbQkuaagYQVnTgtiAqwxUGCZS8ZpWsakgxigVRyQ5wk/I4IVzOHIJqeFcCoR84mCExS+cePGKTElXIqMlS+MgUmcTDVhHhxXc+b0G98LWQQ1THXhe2MuXUCtLME0SNA9mMOJwxzh5DSi4DbFg1YDXR26rBQvLvFF8fKvBcPaZOXLl1cjoRyp5cBCcBMrJp/SsuUCFlxEQwhaxMKyAjidhr/wnFLEqS1BBRdMpUXlm3fv3qkJylzhhy5XokSJ/phNT1eQ1V/pbiVNmlSlYXAmgO/nMLWEq/0ElWUzbdo0lQdHQeZcRpanEYIOESwrgBYLrRhm4lM0TJF5HxBYqYAjbrETJNH2/Bajb9884frZBeHCR6IJprf+jLvbV3hqYhUm3K+TYT86v0G0KJFUUm9QWF6MtbHoI2upzZ07V80xDarPXvBCBMtKuHnzpor10BJhLItBbktbHRSs+QsXYfmpd7CzN3/F0tlD2+P07tVBIlh0AWlZseQQ3zdnGkgibtAjgmVFcKoQ84pYJZXFB1l6l64Xp+xYYhSqX79+WLNuvUUF6+TOlWo+Z2Dyz/wL3Vm6t9u2bVN5UxwIYC4ZRwcl2B48EMGyMjiJmomXLKrHNAXmZXFeoCUEi65pKDt7iwnWxJ6NsG/9AmVdWcK60e4FNdGcr5U/f341gFCwYEFl1QrBAxEsK4QBYI5eMYucGzO4TZVb9TtYoufi5SsWE6xp/Vvi0KZFqFatmkUma7PeFuNUTCNJkiSJWFXBEBEswd8wljNv/kKMW3MCoTVLy9ysmjEM10/uCbKguxD8EMES/A2D0FOnTrWI+2nAkEwaFLXcheCHCJbgb5hWwYC0sTA2xIx25lkZCxe55cK3lhRJIfgigiWYnZMnT6oEzHnz5uktghAwJLFEMDtcbYZ1vTgFRxACgwiWYFaYCrF69WqViLl37169VRAChgiWYFa2bt2qKqYy7YK5Y7JGnxAYRLAEs+K90iZH+5gzJggBRQRLMBssx8LJ2swcZ7Y4p74Yu5CrIHhHBEswG5zjyIVomZbAelcVK1a0SC13IeQiaQ2C2encubOKX7EMcrp06fRWQTAesbAEQbAaRLAEQbAaRLAEsxMxYkS1ak3MmDH1FkEIGCJYgkXgXECZDygEFgm6WwgmTDLTmxUtbY2VK1eq9IYRI0YgSpQoeqvtwHr8CRIk0PeEwCCCZSFYHTRNmjTw1D7t0KFtq4IlF6bw9PSAnZ35i/4FN9y+fkHTpk1VWR4h8IhgWQguwskVkBt1H42/i5bXW20DTsvhCjl2NljBs3XZDKjj6Ogj418IOCJYFsIgWJ3HLEbh8o56qxDSqZTeAY6OtUWwTIQE3QVBsBpEsARBsBpEsARBsBpEsEIIn10+4PSh7di+YiYObV2OTx+c9Z4/w4D4ldOHsWv1XPX8V88e6j1+8+zhHVw+dRAev6ltdevyaVw4tjfQy4+5aO/j7JGdPrY7V8/iw7vX+hGBh6+xbMpA9RkKwRsRrBDAl88u6FTlb2ycPwFvXjzBtmUz0LNuEbx5+efaU0w32LhwIqb1a4Eb50/g0Z3r6FYjP/auW6gf8TNXzxxB77rFcGzPer3FJ58+OmNsZ0e1ffP01FsDxqPbVzG0ZUUsHt8HSyb0VduUPk3RuWoubFky1STrMbq5fsHWpdPU5ygEb0SwQgCzh7RHopR/od+szajddiAGz9+NeIlTKOH6E4/v3sAmTbD6z9mK1oNnoknPcWg/Yh6cRnaGu9tX/Sg/CAWsnjkcX7Wb3TeXTx3Ci8f3tWNMk9keK34SDF9yEGNWHVfb2FUn4NhhMFZOH4LPH9/rRwm2gAhWCID5TY7tBsJOX9yUf2PESYCXFA0NWg9Xzx5Vj8n9m5ewZvYo7dE3ZQ0VKlsLsTVRMJAmcy64fXVVrtKviJ8kpep/dOeq3uIFn0drqGyd1j4SZJ8+uK3cru61CmB0p1o4dWCravfwcNfc0Fm4fPKg2ifOb15ixbTBeP38sd7ik1ChQyNTrqLacz3gpovqZ5ePWOc0Bv0b/4PJfZrgxoUTqt0AxXfzosnoVbeoev19G35tQQrBFxGsEECrgTOQLG1m9ZhxpUd3ruHk3k34p1YL1ZZYs77GdKyFV08fqtjW9P4t4fL+rdYTCmmz5EH9LiPUcYRu0fp54/BX9vyIGiOW3vozYcJFQLF/62siMMWHW3bt3H9KUHIUKq23AK7aOfs2KKEErM2Q2drz6mH20A5YpVloFNdkaTJiXNe6KjZGJvVqpMSQovsrXL98gr29gxLrL59c0LV6Hjy8dRW12vZHuqx5MbxtFRzfs0Ed66mJ4sSeDXFkx2pUa95Dvf7yqYOx3mms6hesBxGsEMQJTaRq5oyKduUzo0LDjkirWUokY67CKFC2BmYObou1c0cjZtyEqNNxqOozQCFrXCQp6uaJjaM71qBup2Fa6+9duqIV6yhL6fWzR3oLcGzXehT4pxrChA2vtwCvXzxBxQYdUaNVHyWeFDM+vnnxpOpPly0fytVti1EdqivLj4Jbs3Xf75OlGWDfs3Y+dq12Uhtd0WGtKyFn4TKIECkKDm9bAXd3N7QbNleJVcmqjdG4x1hMH9haxeiunjmq3NS+0zciW4FS6vWHLdqPRRP6KJdYsB5EsEIQuYqVx6pzLhi98j8VNN+xyiu7OlSo0Cq29VGzqnZo7lfD7qNVnXXvRIgcFXP338fi46808WijAuYfnd/ovX4TN1FyFNSEkK4eefvyGY7tXqe11VT7BhIkTY1C5Wph8+IpWDKxH2YMaoODm5fhwc3L+hFA+XrtEDFKdE2MhmHown2aEEXVe+jOualRyYvH9+HSyQOaG+iKht1Go+XA6cpq+2/nOhTWzu+drPlKKCuS7iXFKkfB0uo9GqBo0yp9fPea3iJYAyJYVg5jQBsXTFCxIwMpM+RA1WbdVZqCYZTO+c0LvHv1HHYOYfBScw0NnDu6Gxc0ITAQVnP1SlVvpomEK+5eu6C3/ppKjTor14vB9w3zxyvrhULmnXevn6NbzXxqNC5z3mIoUbkhMucpqvd6wWt78/wxwkWIpAnTfr3Vi+ix42nWkxM6jV6EjiMXoFabAchesNT3mB0NQTvNPfSOclK1//BzYfzKEOvyjkOYsNp/TTMwIFgGEawQwIppQzTLxmeKwcsnDxAlWkyaV+qmHdOptordtB44AxN7NFQCQR7fva5ZNSN8jAjSPaRlEjlaDL3l18SKlxgJkqVW4nj+vz0oU7uV3vMDupgU0Yqam5opVxGkyphD5X4Z4Gs7jeyCDH8XQq+p6zB3eCd1Xf6FgwTMQfMO0yEcwoZFrLiJkDB5Ws0tPOxD1D99fI87V84iUQqpMW9NiGBZObQyarcbAKcRnbF9+UxcP3dMpTPQ6qrYsJOKA62bO0aJQpWm3ZGzSBnkKfEvJvRooJ5fpLwjXjy6ixkDW+Pe9QvKfRrUvBwKlKmBxKnSq2P+hGOHIZg3qivChA3n53Mia8JJAbpz5ZwaLaQgHd6+Su8FVs4YBue3L5WblzrT36jUuDNGdajh70TOUjWa4dn9W5g1pB1uXTqNk/s2Y2yXOqjbcRhC29khb8lKKnY2pW8zzWo8r97jkJYVUaSCoxJbwXoQwQoBlKndGs36TlIZ7syfYtb6QKcdKo7z4NZl3Ll2Dt0nrlI3L+NZ1Vr0QtjwEZQ7GDFKNIxa8R/ChAuP6QNaKnFjMLvVwOk/XC5fMMcrQ85C+h6QOXdR/K9aE01ounx/TsQoUZGJbp8mmBSMHIX+wYxBrVXKQdI0mdB9wkplUdHSeXLvBtoOno3wESOr51Zu0g05tGs4uX+zur4MOQv+FHPzTrSYcTFrz231/vgaO1fPQduhc/GPJmSE763T6MXK4qQwr5s7GvlLVUGL/l41qtifveA/uosoBGekvIyFsER5GUN6wc+liNn+5zY+X7X89PyA4vM1fr4+Q79f1+edP/X/QL0Hdajfx5v+Pf4eKS9jWsTCCkFQCH4WK+K/NvVck97IPs/18/UZHv/pNf1/TV7n//Xxpn+PgiURwRIEwWoQwRIEwWoQwRIEwWqQoLuFMATd63UapkbABNugY6UcqFNHFqEwFSJYFuLRo0dqmS8PD09fgWchJMO5jI0aNcKMGX8u9SP8GREsC6F9zti4cSPevmWVBNvCzc1NCXby5D6n7NgKpUqVQpIkP8r3CAFHBEswO+fPn8eoUaOwePFisS6FQCFBd8HszJ8/H3v27MGTJ0/0FkEIGCJYgln58uULVqxYoVzhHTt26K2CEDBEsASzQpF69eqVmhJDS8v9NyvtCMKfEMESzMrs2bP1R8CFCxdw7949fU8QjEcESzAbDx8+VLErBtrt7OyUdbVkyRK9VxCMRwRLMBthw4ZFmzZtULZsWUSJEgV169ZFnjx59F5BMB5JaxDMTr9+/eDk5IRz584hVqxfr8QjCH9CLCxBEKwGESxBEKwGESxBEKwGESxBEKwGCbpbCA7p7969G87OznqL7bBq1Srs378fI0aMQOTIXgtN2BIFCxZEggS/XnZf8D8iWBbi8ePHqryMJ0IhVGi/V6MJqXz75qkWdA39i1V4QjLurp/QtGlTTJ3qtUKPEDhEsCyEoYBfrmYjkDRvOb3VNvjm4QFPDzfYhQmnt9gOqxtnQV0p4GcyRLAshEGwivVejFQlzLPMlxD8mF3CAXVlmS+TIUF3QRCsBhEsQRCsBhEsQRCsBhEsG4Qjds6PbuDqplm4tmUO3t2/qtr8i+v7N7izfxUurZmEx2f2wOPrF73n13i6f8XrW+dwae0kXF43Bbf3rsCX96/1XkHwHyJYNsY3Tw+cnNsHuwZUw6c3z/Dq5lls7lwcVzZMZ/6BftSveXP3Ija0zY/r2+bhw7N7OLNwMLb1KAMPN1f9iJ/h0P6B0U3UcQ9PbNfE8ibuHFiNdc1y4tHJnfpRgvBnRLBsjNe3z+Pm7sUoN24vctTvhwIdpqJE/5W4sGosvn7+oB/1a07M6oUURarjn+GbkLf1OJQZtV1ZSrf2LNOP+Jnbe5fjxdUTqDj5CEqP2Ip8bSei5MBVyN9hCg5PbI3Pb5/rRwrC7xHBsjHcXT8ja81uCBs5ut4CRIgRT3PZ3PFN215eP4XjM7ur44iH9vf88lF48N8WtR8rbXak+V9dhAptp/aZWxUlfkp8evVY7fuG5zkysQ1yNRmKyPF9LvOVOHdpJCvwLz6+eKC3AI9O7VLW3+bOJdR1eHz1ug5ybukI3DuyASed+mJVo4w4PL4VPjy9q/qubJyBB8e8rtHA3YNrcW3zj4qngvUjgmVjxMuYHxkqtUGoUPyn/6bE4uyS4YiXqQDCRomOWKmy4vmV/3Bp9QR1/O39K1W8KUH2Ymo/Z4OBiJIwlXr85d1LJWQvr59Esvz/qjbfvNEsutD2YTRhqqS3/IDXkLv5SMROk1Pt39ixAPtH1EeKQlWRrXYPZXmtaZodXz+9/95P8YueLD0Kd52LL84vsXtgDXh6uCthPTG7lzqOMK52YFQjRIiVUG8RQgIiWDbM5k7FsaxWcmVV5W8/WWsJhVB29ijaYwEuaoJ1ed1UnJrbF4W7zYV92PBeT9KheKxunBl7BtdEwU4zET15Br3HJ19d3iNinMSaReb3V00JZ6hQ2nHOODa9K0oN3YSUxWogYY4SKNRlFsJr1t9tb+5mopz/Q6pitRDnr9zI22Yi3j28poQzVck6SsCcH99SxzE2Zx8uIhL//T+1L4QMRLBsGMaxGu/4rIlASWzvURbuX1xUO123Ql3n4MikNvhbc+VialaXb9KUqo86a56i7Ng9ODyhFR4c36r3+EIXo1/BQQAG+11ePUG4qDERI0VGvUf7cmqWWfKClfHs4mG9BYiftYj+CAgXJQbstGMYQwsfLRYS5yqN+5rLSOgKJshWVAmwEHIQwbIxnl/+T6UiGKAoZK/bB59eP9Wsk9t6K1TaQoSYCfD86jF801wuwnSG61ud1NxAA3H+yoWMldvi8topeotPYiTPCLdPH/BZs4J+5puKj93auxzunz96pUf4Gqjk6KOb1ucXjJ8ZYmm0DlMWrYEbOxep0cuHJ7YhR4MBep8QUhDBsjHoKp1eMNBH3pXrhzdqcnL46HHUPlMPnpzbh6pzzuH1zXO4rKc82IePhKNT2muid1QdZ+D5paPKOvKLCDHjI0mesppr2UcTn696qxevtHNfWjMZcdL9raw6XtPrOxf0XqjY1EPNckviz8nicdLnVsLHlAnGriLHTar3CCEFESwbg1bI57cvcGHFaJVq8Pj0buwZ4oj4WYoowaIFtndoHRTvtxzhosVGwU4zcGHlGLy5dxl2Dpo1Vr8fdg+q+T1V4dS8/krc0ldspb/Cz2Sr0xv3Dq/DobHNcP/oRjy9cBBXN87Ejt4VkKl6RxXEDxc1FrLU6oa9g2vhydl9eHHlmJfIuX5BiiLV9DP9njARoqj418k5vfBX+eaa9eig9wghBanWYCGCU7UGBqbp8j3SLCn7cBGQvFAVpClVT7mHTCClG5apagevgzXL6trWufj44qHmYvVX+49P7caF1eOVRRQ5fjJkrt4Z0RKn9Tr+F3DE74omUk/P71dxJfsw4TVXtK9Kk/AasdRO7emBe0c24tbuJSouFSNZBuRsNPh7CsaxGV2RLH9FNaJpgKkNWev0QqTYidQ+Rz2ZzJq7xSiEjfQjdSOokGoNpkUEy0IEx/Iyyi0MFUr7fyi9xf9w6Xntv9/Fxr+wmB/RXlW9tp9o5+b5fzWyaE2IYJkWcQltGApCQMSK8HnGihXhcwypDL+E5w4BYiWYHvlWCIJgNYhgCYJgNYhgCYJgNUjQ3UIYgu4c9Uqc6x+9VQjprG+VRxahMCEiWBbi0aNHSJs2Ldw9PBHQQLdgfTD5tUmTJpg2bZreIgQGESwL4ebmhh07duDNmzd6i+3A9851GZMlS6a32BYlSpSQhVRNhAiWYHbOnz+PUaNGYfHixWJdCoFCgu6C2VmwYAH27NmDJ0+e6C2CEDBEsASz4urqiuXLl+Pt27fKJRaEwCCCJZiVLVu24NWrV2qqjZOTk4pnCUJAEcESzIr34fxLly7h3r17+p4gGI8IlmA27t+/j3379qlAu52dHdzd3bFo0SK9VxCMRwRLMBvhw4dH+/btUalSJUSJEgX16tVDgQI/SsMIgrFIWoNgdvr166fiV+fOnUOsWLH0VkEwHrGwBEGwGkSwBEGwGkSwBEGwGkSwBEGwGiTobiGYMLlz5068e/dOb7Ed1qxZg4MHD2LIkCGIHDmy3mo7FClSBAkTypL5pkAEy0IYyssYcpJsCWa5e3p62tz7Jp8/f5byMiZEBMtCGAr4DR8+HGXLltVbbQMPDw98+fIFESNG1Ftsh2zZssHRUQr4mQoRLAthECyWWOEXWLANHBwcULu2LPNlKiToLgiC1SCCJQiC1SCCJQiC1SCCZeNwBO/GjRu4ffu23vJnOPLFKgwuLi56i9/w3KwyOnPmTFUief369Xj58qVqF4SAIIJlw7AK6OTJk5E7d26sWrVKb/01LA/DxSTq1q2LChUqKPH5Fcw7GzRoELJmzarO/eLFCyxdulSNms2dO1dESwgQIlg2TN68eVWt9YwZM+otv4dWVdGiRZEyZco/JoBu3LhRWVZLlizB7t27MWbMGKxcuVIlkfbu3RsXLlzQjxQE/yOCZcMwxYICwlpVBq5cuYJOnTqpvCnCmuxTp05V9dj/+usvHDp0CJ07d4a9vb3q9wtaYhQllpUpWbKk3uoFrTlaXt7ru3NVnVq1aiFDhgxo164dbt68qfcAa9euxezZs9G/f3+kS5dO1dMyPHfXrl0qXcC7tcbrp/vJaxBCHiJYNkzOnDl/Ep40adLg2LFjSqQILaMVK1Ygf/78SJQoEeLGjavaf8ezZ8/UVrVqVb3FJ82bN0e3bt3UYwoM3UtaeRs2bED8+PFRsGBBJWKEgjVixAhVR4tiWbFiRbRo0ULFxtjWt2/f72s9Mpue52WM7XeCKlgvIliCD3ijc1mu6dOnY9y4ccqtoyUWKVIk/Yg/Q+ssWrRoquLo76DA0HJiVVJaZEys7dmzpxKkYcOG6UcBiRMnRqtWrRA7dmxl/VFUT548qaY6RYgQAcePH1fHOTs74/Lly6hevbraF0IeIljCT6ROnRpjx45Vrt/gwYORJEkSvcd/0EX79OmTEiS/YD/7OGWHo5O+3cbKlSur2JoBBuoN8xD5l1YYA/4Uqy5dumDAgAHqnHQR48SJo2JsQshEBEvwk+3btyNFihQ4cODAL4XnV8SLF09NSWGQ3i8oRi1btlQi8/79++/xMgN8Pf9OlOYy8Hfu3FGjlwzwN23aFGHChNF7hZCGCJbwE4wlbd26FYcPH1ZLc82bN89HYPtPcASxWbNmyq378OGD3uoFq1a0adNGCQ3dz8yZM+PMmTN6rxcUunz58ul7v4fWICeT031lzXjf1poQshDBEnxw6tQpJShcjouuF0foGF+6du2afoT/oKtGS4tpEOPHj8eJEycwY8YMFCtWTLUxIB86dGh07dpV1cliLIuCw8cUnx49euhn+jNVqlRRgwQcGEiaNKneKoRERLAElY/FQDZh/hTTEQoVKqT2s2TJggkTJmDhwoXfXcOwYcOiVKlSKob0K1hKhgmjdP22bdumRu+Yj0UBnDRpkqoLRvLkyYP9+/fj7t27SryY0sBCh0x/IDly5ECmTJnUYwPZs2f3IUy0sMqVK4fWrVvrLUJIRcrLWAhbLi9DoaNLSYvKIFR+wSB8SCvyJ+VlTItYWILZoVBRiH4nViSkiZVgekSwBEGwGkSwBEGwGkSwBEGwGiTobiEMQfeBAwfin3/+0VuFkA7zyWQRCtMhgmUhmInN1AGOmP0p+CyEHFg1gkm0U6ZM0VuEwCCCZSE4ZM8MbhbNszW07xju37+vstJtkcKFC6s5jkLgEcESzA4z2EeOHIlly5bpLYIQMCToLpgdZsnTuuQ8QkEIDCJYgllhxVJaVnSFOeVGEAKDCJZgVjZv3ozXr1+rqTkcKePiFIIQUESwBLPCyc4GWA2UtasEIaCIYAlmgxUYDh48qOYIcuNIKeNZghBQRLAEs8FCfqzBzoUjuDIPq4FKgT0hMEhag2B2WF/LyclJpTdwpRtBCChiYQmCYDWIYAmCYDWIYAmCYDWIYAmCYDVI0N1CcAIwF2N49+6d3mI7rFu3Ti0zz9I6HDm0NbhSEFevFgKPCJaF4Dw6lpfh8n6hQtueYctMd1ssq+Pu9hWNGjVSS5wJgUcEy0IYCvjV7zwcOYuU1VttA09PD7h+/oTwEW3PumpfMRvq1JECfqZCBMtCGASr85jFKFzetpb5smUqpXeAo6Ms82UqJOguCILVIIIlCILVIIIlCILVIIIVQvD08MB/u9Zh1Yxh2L9xCVy/fNJ7/gxH8B7evoIdK2dj08JJePrglmr7Fe9eP8elkwdVIP1XPL53A5e1Y353Hv/w6eN79Vret6tnjmiv7aIfEXi+aOfauGAivnwy3TkF8yCCFQJ4/uguWpZOh0NblsPDwx0HNy9FuwpZ8NH5jX7Er6GgLBrfG0NbVcL9m5fwQNs6Vs6JdXPH6Ef8zNnDO9GrTmElHH7B1+1eqwBGdaiBb56eemvAeHjrCgY1K4uN88dj86JJalswpgeaFk+BXWuc9KMCxxeXj1g1cxg+f/qgtwjBFRGsEMDaOaOQvUApdJuwAjVb90PvaRsQO34SbJg/QT/i19y7fgEHNIts6MK9aNZ7IloPnoXhi/dj5fSh+PTBWT/qZ5hLtkI7hnlGvjm0dSU83d21g0yTdxUjTgJ0GbcMPSatVtuIpYfQY/IarJw2RFlggu0gghUCSJY2C8rWaaPvAXb29kiWLgtePnmg9pdPGaS5UgfUY3Lz4klM6dsMH9691o51QOOe4xAzbkK9F4gZj1nZ3+D57dfWUZyEyfD+zUvlonnHw90NBzYtQdF/6yF0aDu9FXj9/DEm9WqMTlX+Ru96RZX76fb1i7IIV84YioOadWhwHylC47vXx6tnv160In6SlPjs8kGdg7ho4jpfs7x6apbfmM6OOL5now93lOecN6orutbIp15/7/qF2nNd9V7BWhDBCgGUrtUCiVKkU3Gdd69f4NT+LTi+ez0Klaup+jP8XQgTezTA47vXVdxpRLuqSJUhByJHi4kkqdIjX6kq6riPzm9x78ZFTOvXAnn/VwWRokRX7X4RIVIUVG7aVXPRJvsQhhsXTsBZu4achcvoLcDXL58xpEUFxEucAl3HL0O9TsOVVbhj5RzY2dkjX8nKWDi2Jx7duaoEaGiriogQMbKyrH4FxYzXYO8QVhOrd5oLmh9fPn1Eq4EzUKJKA+Xmbl/ulV3+1fUzBjQprUSz0+hF6vU3zBuHqf2aq37BehDBCkHcvHRKE4bymiBVQ+HytZE1n1d1z0y5C6N8/Q6YMbC1slzSZsmDklUbqT4Dnz46Y2wXRwxuXh7PH91BnQ6D9Z5fQ1G6cvownN+8UPu0lpZOGoBKTboiXIRIqo24aOcuXqUhqrXoqVlGqZA2ax5UadoDBzd7rVNIsa3UqDNGd6yFLUumqdWxm2ruaWh9ChOto/0bF2PPugXYvWYenEZ2xqBm5fB30fKIqInWrlVz1Tno0iZO+Zd63x1HLcAyzbJklv2p/Vvx/u1LNO87WVlmfP2BTjuVsD+4dUW9hmAdiGCFIDLmLIRRK/6D04EHOP/fHiyfOkhrpfUTCqWqN1XxJgbV24+Yp1xB70SIFBX9Zm7G7N23UahsLfR0LPzHkcaoMeIo0Vo9a6TaZ/D6zcsnPqwrEj1WPOT7X2UVU5sxqI0SRQbR37995XVAqFAo49hauZnLJg9A60EzEdruhzvprrlu9zXLj/E2DgxEiR4bA+ZuR5Ne49VzKZppMuf28ZyEydNq1/MBzx7ewdMHt5ExVxFlURqIFjMOYsVPrAYsBOtBBMvK4ZD8zlVz8IEjgtrNS6skSvRYqN6itxKtb55e7tr7t6/Vjev85iVuXTqt2sjVM0e/7zOQzpu+UuMuav/mhZPq7++o3rI39q1fqFxRxqUSJkvzkyvHkT6OGrq8f6uEq1a7AajQoIPe6wXjYY/uXFOW2ZN7N/VWL6LEiI36XUaicY+xaqvarAdSps+mvV2voD5dQi9h9oa+y2PoslKQfcM2U6ZHCOZHBMvK4Wo0a2ePwplDO/QWL66dO6bd/BGViDE4PbVvU1Rs2BHthjtpj5t5CZzGLc2NZLyHeVwGGIz+5PL+tzEkA3TF/i5aTrOemHYwGTXb9Nd7fnDh2F6kzJAdju0HI3OeYkjxV1ZcPnVI72Wg3h1jNHe0QOnq6DtjEyb3bow7V8/pvX8md4l/cXjbKh9BdA4y8PrjJkqBdJoLePrgVvU5GGCeGGN6iVOl11sEa0AEy8pxCBMOdTsNxYyBrXB051pc14RqycR+KuBco1VfZWGsnDFMuUPlHNsgd7EK6gYf0baqusELl6+lLJ/5Y7rj6tmjuHh8PwY1L4fMuYsiQbLU+qv8noKla2DjgglIljaTEiPfRI0ZV41MXtPO//D2Vcwb2VW5d4Qxpo0LmbT5UcW4UmXMgTodh2Ja/xaawHxUx/yJklUawd4hjPaclrh9+TQObV0Op5FdUKN1X2VxpsuWD3ETJsfkPk01If9PjWyO6VQbRSo4ImnqjPpZBGvArm/fvgP0x4IZcXZ2xqRJk5RLlCxtZr3VNCRJlQHJ02VR+VT/aaIVIXJUtBk8U7lNH987KwunYoOOiB47vjo+Q86CePPiCaLFiqviRtkK/oP71y+qgPb9G5eQSROreppo+I5zGaDraK/18TwkbuLkKlBeqkbT7+kRTBilx5YpTxE1EhklehxsXTIVV04fQfaCpVC5SVetP7R2jdk162cbGnQdiajRY6vnJtc+n1dPHyFM2LCIGS+REtbMuYv4iFF5xyFMWBQsUxO3Lp9SwflHt69p1twg5C5eUQk2n8eSPq6fXDQhn6mJ2hklVv827KRSL3gdzHLn++a5TMmKqZpVmTkTKlSooLcIgUHKy1gIS5WXocXiPf/JGL59o8iYz+g2pD8EZSE/XoMlX1/Ky5gWcQlDGAEVK2JOsSIUiqAUKxLUry8EDhEsQRCsBhEsQRCsBhEsQRCsBgm6WwhD0J2jV9kL/qO3CiGdrtXzyiIUJkQEy0I8fvwYadOmhbsquyKGra3g6eGOZs2aYcqUKXqLEBhEsCwE85SOHj2K169f6y22g/Ydw507d5AuXTq9xbYoUKAAYsb8MY9RCDgiWILZOXPmDEaNGoXly5frLYIQMMQ3EczO4sWLsW/fPjx8+FBvEYSAIYIlmJUvX75g6dKlePv2LXbt2qW3CkLAEMESzMrmzZvx5o1XZQiOlDGeJQgBRQRLMCuzZs3SHwGXL19WwXdBCCgiWILZuH37Ng4fPgx7e3u1caR0/vz5eq8gGI8IlmA2okePjh49eqjSKlGiREGbNm1Qvnx5vVcQjEfSGgSz069fPzg5OeHcuXOIFSuW3ioIxiMWliAIVoMIliAIVoMIliAIVoMIliAIVoME3S0EEyY3bdqkFqOwNTZs2KDSG/r3749IkX6sCG0rFC9eHEmTJtX3hMAggmUhHj16hNSpU8PD2/p/gm3QsGFDzJw5U98TAoMIloUwFPDL3WIUkua1rVwkrlTj4foJ9uEi6i22w6qGGVFXCviZDBEsC2EQrGK9FyNVCfMt8yUEL2aXcEBdWebLZEjQXRAEq0EESxAEq0EESxAEq0FiWBYiuMSwvro44/HZvSwyr7f8IG6GfIgQM76+9zPvH9/C69vn9T2fJC9UWfvvr1dV/vT6Ke4d2YBPrx4jYpwkSJSjBCLHT673hlwkhmVaxMKyMVxePcG1TbNxddMsb9tM7B/RAA9PbNeP8ps3dy/5et4sXFgxFrsH1VAjgb/i8vqpWN04M+4dWqtpWig8PX8Qqxplwql5/fDND+EUhF8hFpaFCM6jhG/vXcb2nuVQedYZhI0cXW/1H6ec+uH1nQsoNWSdtvezhfX23hVsaJMXJfqvRKK/S+mtwBfnV1jbPAcKdJyOJLnL6K1eeLi5ws4hrL73M54ebggV2k7TvuD/eysWlmkRC8vW0SyjKxtmaC5dVSVWj07txPFZPeDp7lXK2NPdTe3fP7pJ7XvH0+0r7hxYhYyV2mp7fruDp+b3R+bqnX2IFQkXNRbyt5sC54c39Bbg5fVT2DvEEZs6FMWewbXx6sZpvQe4e3AN7uxfievb5mFL5xLY0buiulZeP6/t9PwB+pFevLh6Qonp7yw/wfoQwbJxvn56j4cntyNl0epqP37mQnh57QSOzeim9s8uGooXl/9D/KyF1b53HhzfCrsw4fzsM/Dw2FYkzlVa3/NJ0nzlkalqB/X45bWT2KO5lok1a6torwVImrccdg2o/j1mxr8nZveC+xcXFOoyBwmyFtXc2Ib49OYZYqXOhvPLR8H58U11LLm4egJcP77VrLBfx9UE60MEy8a5vW8FIsVOhFhpcqh9ClCx3ktUvOnSuim4c3A1ivVdijARoqh+A1zRmP3py7dAaDt7vdUnn9+9UO5d+Ohx9Ba/4bkOjm2GjFU6IHXJ2oiaMDVSFa+FtGUa4czCQfjm6TWdiQMCGSq1QdREqZG5WkdEiJVABfIjatcfPXlG3D+8QR3n8vIxHmpimrKIlwgLIQcRLBuGQnB9qxOSaNZMqNA/vgoUhgKdZuDYtE7KnYsYK6He8wOXFw/h/OCqPjroN3YO4VSQ/U+4f/4I1/dvkLxgJW1PP157XorCVfHm9kW4u35RTQZRVWj9EbXrdHn5SO1mqdkNN3YsUI+fXjiIaEnSIU6GvGpfCDmIYNkwH57dU6kKaUrV11t0vn3D84tHlOXy6OQOZQH5hi5Y4txlES5abL3lZ8JEjIIoCVLi/rEteotPbuxYiD2Da6k407dvnirlwjuULrZr//Xa/434JchaBF800XN+dBP3NasrbZnGv7T8BOtFBMuGYaA6VYnaKgDunevb56uAdvnx+/D+6R0lLBQxA18/vsPDEzt0i+j3ZPi3NS6tnqhiTd5xd/2k0hoS5SgJh/CREC1xWjw+s0fv1WAw/b8tiJo4Dew1N/VPhIsaUxPQ0ri5e4kK3vvn2gTrQwTLRvn89gXuH92I1CXr6i1eMPjNuNHfTYYhUtykKNJ9Hs4uGoyXN8/oR0AJS9goMZAgezG95dekK9tEWWoc2bu8biqeXTqiRvo2tCmAuJrLRsEMbe+APC3H4NKaSbi2dS7ePbiG8yvH4trmWchRfwBC+ctSCoVUxWri4qrxiBwvGcJGjqG3CyEJESwbhZZTurJNETvd33qLF7f3r0K2un2QKGdJtR89WQZNvIZqruFO5Z5x+/j8gQp+/y5XyoB92PAoPWKLijE9PLENx2d2U5n2uZuPQJEe81WQn8RMlRWlhmxQaQ4HRjfR/l5HyUFrEeevXKqf1+H7WpkqYegnzNRP80995G09zkdMTgg5SOKohZDyMraJJI6aFvkZEgTBahDBEgTBahDBEgTBahDBEgTBapCgu4UwBN3/bjxE5QsJtsG6FrlkEQoTIoJlIR4/foy0adOq9QkF26J58+aYPHmyvicEBhEsC+Hp6YkzZ87gzZs3eotgK+TOnRtRo0bV94TAIIIlCILVIEF3QRCsBhEsQRCsBhEsQRCsBhEsQRCsBhEsQRCsBhEsQRCsBhEsQRCsBhEsQRCsBhEsQRCsBhEsQRCsBhEsQRCsBhEsQRCsBhEsQRCsBhEsQRCsBhEsQRCsBhEsQRCsBhEsQRCsBhEsQRCsBhEsQRCsBhEsQRCsBOD/uMwa0ZVqrasAAAAASUVORK5CYILLC2IidC+zrkHr5KPXb+lceWtKX2PR+kE4RHwIh4BBOAwnYSUdbKysMGPHlAlOIfOlSWDqRbiRc6bDW1rWej2yxrz58q6h2+FQaF3InCAcIj6EQ8AgHA6OhA0JQ/KxKHj0Sr/WkD7vUM9t5/P6UT2EQ8SGcAgYhEMAZREOERvCIWAQDgGURThEbAiHgEE4BFAW4RCxIRwCBuEQQFmEQ8SGcAgYhEMAZREOERvCIWAQDgGURThEbAiHgEE4BFAW4RCxIRwCBuEQQFmEQ8SGcAgYhEMAZREOERvCIWAQDgGURThEbAiHgEE4BFAW4RCxIRwCBuEQQFmEQ8SGcAgYNhyOW3PzZIVt9gOAXPozg3CIWBAOAcOGQwAoi3CIGBAOAWONNdZwf+ADQIiHHnrI/dkC1AnhEDDuuOOOZMqUKcl2220HDLDeeuu5xwFx4YUXuj9XgLohHAJAoD322CN555133D4AiAXhEAACvPHGG62/Sb300kvdfgCIBeEQAALIrwzlb8q22mortx8AYkE4BIAAm2yySftJB88995xbAwAxIBwCQIFf/vKX7WAoTj75ZLcOAGJAOASAAscdd1xHOFxsscXcOgCIAeEQAAosvfTSHeFQ3H333W4tANQd4RAAcvzgBz8YEAzF/vvv79YDQN0RDgEgx6c//Wk3HI4aNSp5++233TEAUGeEQwDIIK9t6AVD9e1vf9sdBwB1RjgEgAwXXHCBGwrV5MmT3XEAUGeEQwDIsPHGG7uh0Hr22WfdsQBQV4RDAHCkX9tQ3jrP/lvxmocAYkM4BACHfW1DCYY2HE6aNKn9+YQJE9zxAFBXhEMAcJx++unJfPPN1wqAe+yxRzsMir322qv9+Sc+8Ql3PADUFeEQADJ88MEHyZVXXtn63D5yeO2117aeqfzb3/52wBgAqDvCIQAESIdDrwYAYkA4BIAAhEMATUE4BIAAhEMATUE4BIAAhEMATUE4BIAAhEMATUE4BIAAhEMATUE4BIAAhEMATUE4BIAAhEMATUE4BIAAhEMATUE4BIAAhEMATUE4BIAAhEMATUE4BIAAhEMATUE4BIzvfe97ybbbbptsttlmQAcNhmLllVd2a9BsZ511lvtzBagbwiFgrLTSSh0hAADKuO+++9yfLUCdEA4Bw/7qEADK4k8OEAPCIWDYcLjNNtskU6dOBVr22muvZOLEickOO+zg9qO5CIeIDeEQMGw4vOGGGxIajUYrajxZCbEhHAIG4ZBGo5VthEPEhnAIGIRDGo1WthEOERvCIWAQDmk0WtlGOERsCIeAQTik0WhlG+EQsSEcAgbhkEajlW2EQ8SGcAgYhEMajVa2EQ4RG8IhYBAOaTRa2UY4RGwIh4BBOKTRaGUb4RCxIRwCBuGQRqOVbYRDxIZwCBiEQxqNVrYRDhEbwiFgEA6712bNmpWceuqprY+9bnou0e0mc2+xxRZt8r0hH3t1Plr9GuEQsSEcAgbhsDtNQpPuY68DlD2XhLZuNQ2FOnceQmKzG+EQsSEcAgbhcGjNC1S9DE42GIpuhUNvXiHH7aOU6RpaMxvhELEhHAIG4XBwLR0K7ecSorrZNJzp/FY3Alp67qL123oCYjMb4RCxIRwCBuFwcE33TGhA0n93OxymQ6gNpt0IZ+m5Q5oNiKFjaPE0wiFiQzgEDMLh4JrsVzpM6T72IhwKO6/8W9cwlGZDXtl1d2sNtPo1wiFiQzgEDMLh4Jr3aJnuoxey5JjKazJvus47V7eCWd6ai5qsS8d7a9QmfbJOXbOer+xe6Dw6h5B/e/OkxxY1rc27Dtp/GuEQsSEcAgbhsHtN99ELJHJM+7MCiK3x5rBNQ5J8HGyTdYSeb7AtHebSpD9rP+w12r3xpNdvr60o8Nm5aWGNcIjYEA4Bg3DYvab7mBW0bNhJt7JBLW+u0NbrUKRr1HVqSJOP9tzCC3D2GtNzSJM57DnSc9hxeU3Hh+w77f8a4RCxIRwCBuGwe033MStkSHjJqtHjRUFGW2jwyWs2oHW72bm94Kct7zq0L6tfW9YcIWvI+5rQshvhELEhHAIG4bB7TfcxL2R4gcUeC21ZgahM0/MOZY6sptdTFLhsOEsHOL1Gr882O4dteXNrG8ze0wiHiA/hEDAIh91ruo9FgcgGEhuAisbZ1o1w2I05vFY2cGWtQ48XzZMXAouuUceV2Xsa4RDxIRwCBuGwe033MSRo2OATOsa2otAT0roxh9c0HIbOmxUmy6xPx6fDYV5wtOdN99HyG+EQsSEcAgbhsHtN9zEk6NnQIsq2bgS7rFA21KZrC9kHaXYvbOtGOJSmfel59PqHsodNbYRDxIZwCBiEw+413ceQUGSDmSj7yFWZ4JTVbCgre35tMk6uxY4vuza7DtvKzKPjvevImkfHhIZY2n8a4RCxIRwCBuGwe033sShs2GCowUWUaWWCU1azoWywAckbX3Ztdj9sKzOPjvfCob1O7c86Jy2sEQ4RG8IhYBAOu9d0H4uCVrqubJiSNpgxXtN5RNmWFbD0eOjasurLXKOuwwuH0tJz6Tn1a0Ar1wiHiA3hEDAIh91ruo95gUNDitA2mEfwygSnvDaYc0vLG2f7ssKabVnzlLnGovPZNUnTz8tcM+0/jXCI2BAOAYNw2L2m+5gVOOS41qRDTF6f17oVDqXpXCIkLNmglXX+0PXZ60630Dmk6Rwh4VDnFbTBNcIhYkM4BAzCYfea7qMXsGwIygpgZUJLmeAU0uy55XNZYzpoyb9tnchqNoyJ9DWn5/L2RPvlY1HTedJrti299qyvA624EQ4RG8IhYBAOu9d0H73Qkddnm9YVBaIywSm0ydr0/FY6VOmxvCAmLR0QdVx6vqw90Tr5WNR0rrw1pddDG3wjHCI2hEPAIBx2r+k+psOODUNFzQaYvCBZJjiVaXLOrJAo5HxFoTDdsuYrmqvMNeqcRWuz56YNvhEOERvCIWAQDmlZTYKW1Y3Wzblo/WuEQ8SGcAgYhEMajVa2EQ4RG8IhYBAOaTRa2UY4RGwIh4BBOKTRaGUb4RCxIRwCBuGQRqOVbYRDxIZwCBiEQxqNVrYRDhEbwiFgEA5pNFrZRjhEbAiHgEE4pNFoZRvhELEhHAIG4ZBGo5VthEPEhnAIGIRDGo1WthEOERvCIWAQDmk0WtlGOERsCIeAQTik0WhlG+EQsSEcAgbhkEajlW2EQ8SGcAgY9of8Kquskmy++eYAkEt/ZhAOEQvCIWDYcAgAZREOEQPCIWBstNFG7g98AAjx9NNPuz9bgDohHALGM888kxxzzDHJEUccAQywzTbbuMcBcdttt7k/V4C6IRwCQKAdd9wxee2119w+AIgF4RAAArz88sutXxt+4xvfcPsBIBaEQwAIcNZZZ7XC4QYbbOD2A0AsCIcAEGDixIntJx089thjbg0AxIBwCAAFHnzwwXYwFJ/5zGfcOgCIAeEQAAoceeSRHeFwgQUWcOsAIAaEQwAoMHbs2I5wKG655Ra3FgDqjnAIADmuu+66AcFQTJkyxa0HgLojHAJAjh122MENh+Kvf/2rOwYA6oxwCAAZ9LUNs5x33nnuOACoM8IhAGTQ1zbMsv7667vjAKDOCIcAkGGttdZyQ6H16KOPumMBoK4IhwDgSL+24YgRI9qfjxw5sv350Ucf7Y4HgLoiHAKAw7624dxzz90RDjfddNP25+PGjXPHA0BdEQ4BwPHNb34zWW211VoB8OCDD05mn332diA8/PDDWx/nnXfe5NBDD3XHA0BdEQ4BIMdPf/rT1kf7yOG1116bPPDAA8n7778/oB4A6o5wCAAB0uHQqwGAGBAOASAA4RBAUxAOASAA4RBAUxAOASAA4RBAUxAOASAA4RBAUxAOASAA4RBAUxAOASAA4RBAUxAOASAA4RBAUxAOASAA4RBAUxAOASAA4RBAUxAOASAA4RBAUxAOASAA4RBAUxAOAePcc89N1lhjjWT8+PFABw2GYpFFFnFr0GzTpk1zf64AdUM4BIylllqqIwQAQBl33HGH+7MFqBPCIWDYXx0CQFn8yQFiQDgEDBsON99hz2S/z58FtOz52VOT9Sd/Mtlh3+luP5rrQx/i71ERF8IhYNhweNx5NyQzX0gAIBdPVkJsCIeAQTgEUBbhELEhHAIG4RBAWYRDxIZwCBiEQwBlEQ4RG8IhYBAOAZRFOERsCIeAQTgEUBbhELEhHAIG4RBAWYRDxIZwCBiEQwBlEQ4RG8IhYBAOAZRFOERsCIeAQTgEUBbhELEhHAIG4RBAWYRDxIZwCBixhcM9pp2arDZpi/Y1Cfm3HPfqe+GMq2e1zmnX0c01yPwyl/JqQnVzrl6waysi1+LNUUWyXv3e8PqrjnCI2BAOASOWcGhvtnl6GSA0FHrntWSt3vhQ6Wv1akLZeWTtXk0/2fWFGur+DgfCIVAthEPAiCEc2hutBBwJaRoC5WO6Pz2+W/QcQs6p60ivQej6BqNbc6XnqXI4lLXJerNIf9WvxZI161q9/qojHCI2hEPAiCEc6vrlhuv1CwlQWteL4BB6s7chxusPYc8lBns9dQhUura8r61l92YoAbzXQr9fqopwiNgQDgGj7uGwzE1Ww1C3Q5ANnkUhxtZ26xG/wczlzRFDOBS9+jp3U5nv2yoiHCI2hEPAiCUchgQBG8y8/sEqc6PvdjgcbBDSOeRjlcOUXqes0+v3lPl69Esd1piHcIjYEA4BI4ZwKEKCVtYNWY5LMJKP9nia1gl7Pvk8dA1C19CNcChzDGY+HaPXJJ/nhUOZW+ssOZa1bzpGFK1N69Jz6XmyzuGx++P1C7s2rdXzl9nH9Bx2Hq9ehayxygiHiA3hEDDqHg7LyLohSxjQ41k39ZCaEN0IBek5NJzIx3Stp+x4W5/HC1U6d1a/sPOna/S41NjjedLXl9efpeh8sk57bR7pD7lmr7/qCIeIDeEQMJoSDu3N2Lvx237vhq59WQEqhMyr8xSFjzzpYGHnTdd6tFbXoCHHuzZ7Lvk8vTe2P2tvysyf7s/ry6JzeufTteic9nrk86L1CFsj8vbE60/XpPvqgHCI2BAOASPGcCg3YyU34XQg8MYIW2dv6PZG7t3os2StwQstZXjBQufPuz6RN9Zbl9bmzSvXqHXe/th+O0/WcauoP81eX3pMXp9l67zrydsvJePy6uw50n11QDhEbAiHgBFjOLQ3Xsu70aelb+ihgSLNBh8rZA1FvGARGja0xl5LVojRgJM+7vHmtez6dA+yzmsVzStkPl2r1ot0XchcKmtt9jqK5pE1aa1es7Lz2ON1QThEbAiHgBHrI4dy8xXpwFDmhm5v4EXj0tJrsOsoO1eaXZc9rsfSQURljcsKQmWEzJHeA/3cq1VaU4acJ70H9utqj2fJqg+5TiurPvT6q4pwiNgQDgEjxnDosTdj+dyrUbZWhAaBInbeocyZFSyygojScenrLxpnSWhSMo/S9RTNoedS6bWk2do8Mq+QdXnz2DV6/Wk2HNo5df1F61ZaLx/t8bLrqRrCIWJDOASMpoRDYW/IWSFC6U1deP2DlRU6ysgKFkVza1862GQFGCVz2f3IkzWHsmsvqhVam15zWXrekHMqPbfdy7LryTqv3Qd7vC4Ih4gN4RAwmhQOhV5rXjCzN25RJlCEkPmGMm9esMiaezBjhLcXckzJPtrw6M1haZ3K+zoIrZNzef2hQtdneWv0juWx+xdyvC4Ih4gN4RAw6hwONZSI0Ju1Xmte2NAaG2Ty6suuQeeVj15/kbxgIWvQPrsePeZdR9Z67Hnyrl+EXJOdL6ReaH3R+YvYc3v9aVn7qOsOXY+eN32dZddTNYRDxIZwCBh1D4e6dnsDz6P1WTf3dGixN/Gsc6THFNH60ICRVhQs8q4hXSuy1q/j0sc9On9WrV2DXnfRGJEeM1hlv1ey9ixrr7JofXr9WfPXBeEQsSEcAkadw6Eoc7O2N2QvIGT1F52jzBqEniMdGEIVBQsbhOTf+nnW+bLWXzRO2fVk7YE3l11n1jmK+svQuUK+TlnntWv2vocsuy/peWyfPV4XhEPEhnAIGHUPh3k34DSt88JB0Tx5Y0NCjrLn8fpDhMyh/bLeolqtSV9b1nHLXntWrc4j0n32WrywpX1F+xrCnitvvqI1heyL0DrvXPYc6b46IBwiNoRDwKh7OBQ2fKRvxHJztzdiMZgQYkNQ0c1ePk/XyPi8dZZhz+X1C3uuovNprXz0jmeNt+vImsPWePsussYKHZu3/jLyrin9vZJ1Tvu9IPN582i/8K7bnifdVweEQ8SGcAgYMYRDoddQxLtR28CQ7rPsDb3ohp8nK3SECgkWIQFF5YUzuzfyubLHZG5dk/xbx9p15l2zXasdL0LGl2XXlaXofN4cdl/031n7bsd7/VVHOERsCIeAEUs4FHLDTd+ghRzLutnLzVv682osPUdWrRwX3hpEXkgLZdfs9auitaqiuqzrsfW6JntM/h1yfiE1Wm/3qMwcZej5vOsq8zXy5tE1e/Uq9GtYVYRDxIZwCBgxhcO0Mjf5XqnCGroptuvppibtDeEQsSEcAkbM4RBAbxAOERvCIWAQDgGURThEbAiHgEE4BFAW4RCxIRwCBuEQQFmEQ8SGcAgYhEMAZREOERvCIWAQDgGURThEbAiHgEE4BFAW4RCxIRwCBuEQQFmEQ8SGcAgYhEMAZREOERvCIWAQDgGURThEbAiHgEE4BFAW4RCxIRwCBuEQQFmEQ8SGcAgY9of8fAsukiy65LIAkEt/ZhAOEQvCIWDYcAgAZREOEQPCIWBsvfXW7g98AAjx+9//3v3ZAtQJ4RAw3nzzzeTcc89NzjjjDGCAXXbZxT0OiMcee8z9uQLUDeEQAAJttdVWPDIEIHqEQwAI8Nxzz7V+bSiPEHn9ABALwiEABDj55JNb4XD11Vd3+wEgFoRDAAjwkY98pP2kg1mzZrk1ABADwiEAFLj77rvbwVDsvPPObh0AxIBwCAAF9t9//45wOHr0aLcOAGJAOASAHG+//XYyatSojnAorrrqKrceAOqOcAgAOS699NIBwVBsu+22bj0A1B3hEAByTJ482Q2Hgtc8BBAjwiEAZHj22WfdUKhOP/10dxwA1BnhEAAy6GsbZllttdXccQBQZ4RDAMhgX9swC695CCA2hEMAcNx1110dIXDEiBHtz+WlbPTzww47zB0PAHVFOAQAx3777dcOgIsuumhHONx6663bn88333zJBx984M4BAHVEOAQAx/e+973Wy9VIAJw+fXry4Q9/uB0IZ8yY0fq46qqrJqeddpo7HgDqinAIADl+97vftT7aRw6vvfba5PXXXx9QCwAxIBwCQIB0OPRqACAGhEMACEA4BNAUhEMACEA4BNAUhEMACEA4BNAUhEMACEA4BNAUhEMACEA4BNAUhEMACEA4BNAUhEMACEA4BNAUhEMACEA4BNAUhEMACEA4BNAUhEMACEA4BNAUhEMACEA4BNAUhEPAOProo5MFF1ywFQQAS4Oh8PqBnXbayf25AtQN4RAwJBjaEAAAZXz/+993f7YAdUI4BAz5v3/vBz4AhOBPDhADwiFg2HC42q7Tk8mn3AC0rbXnCclmx17m9qG5PvQh/h4VcSEcAoYNh/JD/9BZCQDk+pD5uUE4RAwIh4BBOARQFuEQsSEcAgbhEEBZhEPEhnAIGIRDAGURDhEbwiFgEA4BlEU4RGwIh4BBOARQFuEQsSEcAgbhEEBZhEPEhnAIGIRDAGURDhEbwiFgEA4BlEU4RGwIh4BBOARQFuEQsSEcAgbhEGVtf94s9ziag3CI2BAOAYNwWGyd/U5Nxq21RWndClHe3CG8uQZDrkPm0+8TS47L/njjEC/CIWJDOAQMwmGxrGBUpFuhyZs7hDdXGXmh0ENIbA7CIWJDOAQMwmExCT1l6H7K5958ZaXnz2PDnDdXKAmGOo/QRwjto6HyuRyzdfJvOw/iRDhEbAiHgEE47C4blrz+XtNzDzWk6Tyhc9nrJiDGj3CI2BAOAYNw2F26l/0ISDag2Uf4yhrsPPqopXz0+hEPwiFiQzgEDMJh99hQ5fX3mp5/qMFUr6HsPPZX0aGhUuqGEmRVt+ZBGMIhYkM4BAzCYffoI2fpUCWhRfr07/ZsX5rWCa8/j34dhxIOZazO4/UXkfFF16k1eh5VNM7uox7z5pE50kGxzNdAlKltIsIhYkM4BAzCYXdI+NB99AKFHNP+dHApU5PFjvX6Q2nY6lUosusUej4r69x2j+Xfdqw3T3oPtUY+2uNpRV9LEA4RH8IhYBAOuyMknNkAkw4udvxgAslQxlrdmsdTdI223wtwNrRJv8jbx/Qcdnx6nGXn8PpBOER8CIeAQTjsDt1DL/RYGhDTwSV0vKebYUbnyQtPg2HXmHeNti69BhvuhO2z8kKgHk/vv6U1g/laNAXhELEhHAIG4XDoyoQzG1w0fOj4vMCSRwPnUMNMXqgaKp03ZI1ZAdrbuyxZdTq3sMeVfi28sfgPwiFiQzgEDMLh0On+hYYJG0BsWBlMICsTmIr0KhyWXWPWOsqsLyRgenPYr026D/9BOERsCIeAQTgcGhsmyoQzGwrLjrW6GWbKhK8y7Lxev8dbR5l5ssJhUZ/OP9ivR1MQDhEbwiFgEA6HZijhTMd5ISWUztGtMKPzdTMcDmaPtN5eV7fCYdZ6hvK1bBrCIWJDOAQMwuHQ6N6VDWc2iAxmvOhFmMkLVSFkTTLWjh/MOrXe7ku3wqGdx4ZgXac9J3yEQ8SGcAgYhMPBG0zoEXac/bzso3V2Dq9/MDRUCa+/iLemrDCWx6u389haT144zOrXubu5n7EiHCI2hEPAIBwOnu5bmTBhw6COKwoyHm+ebrABrOy8dk1Zoc4ezxIyj633FO1pei57znQtBiIcIjaEQ8AgHA5OVoApomPSwUuPhwbEXoYZDVZiMNfmXUNRWLP02tK13QyHQueSebU+/XWBj3CI2BAOAYNwODgh4SMtL9DZ4BMSUMrUlmXXEnIOG66E/NurCZnP7lG6zs5hj3tCvj62Ruf11o6BCIeIDeEQMAiH5YUGHSsv9Hg1eSHF1nn93WDPIeTfSvplfcIGKxG6bvnc1qbn0vNYUqP96b40G/y8fmHnC50X/4dwiNgQDgGDcFieDTlef1o6FHk1KiTUhM41VOnAlkfqbNjLYvciS9Z1dTscCnt9vd7PmBAOERvCIWAQDsuTQCFCw4TWC6/f0kCWNX9Rfy/IeYR+nyhdR0gotKRe5pOxZeay1+71Wzp/0R5pXcic+A/CIWJDOAQMwiGAsgiHiA3hEDAIhwDKIhwiNoRDwCAcAiiLcIjYEA4Bg3AIoCzCIWJDOAQMwiGAsgiHiA3hEDAIhwDKIhwiNoRDwCAcAiiLcIjYEA4Bg3AIoCzCIWJDOAQMwiGAsgiHiA3hEDAIhwDKIhwiNoRDwCAcAiiLcIjYEA4Bg3AIoCzCIWJDOAQMwiGAsgiHiA3hEDBsOGz9wAeAIvozg3CISBAOAaMjHAJASYRDxIBwCBg77bST+wMfAIrI/1y+9tpr7s8WoE4Ih0DK97///db//QNAGQRDxIJwCAAAgDbCIQAAANoIhwAAAGgjHAIAAKCNcAgAAIA2wiEAAADaCIcAAABoIxwCAACgjXAIAACANsIhAAAA2giHAAAAaCMcAgAAoI1wCAAAgDbCIQAAANoIhwAAAGgjHAIAAKCNcAgAAIA2wiEAAADaCIcAAABoIxwCAACgjXAIAACANsIhAAAA2giHAAAAaCMcAgAAoI1wCAAAgDbCIQAAANoIhwAAAGgjHAIAAKCNcAgAAIA2wiEAAADaCIcAAABoIxwCAACgjXAIAACANsIhAAAA2giHAAAAaCMcAgAAoI1wCAAAgDbCIQAAANoIhwAAAGgjHAIAAKCNcAgAAIA2wiEAAADaCIcAAABoIxwCAACgjXAIAACANsIhAAAA/n//k/x/71DSjR6g0okAAAAASUVORK5CYII="}},"cell_type":"markdown","metadata":{"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"E4C63967592040D9BD9D31D7078999DC","mdEditEnable":false},"source":"### GoogLeNet模型\n完整模型结构  \n\n![Image Name](https://cdn.kesci.com/upload/image/q5l6x0fyyn.png?imageView2/0/w/640/h/640)\n"},{"cell_type":"code","execution_count":16,"metadata":{"collapsed":false,"jupyter":{},"tags":[],"slideshow":{"slide_type":"slide"},"id":"566939FB07C646D380806E2CA941FD85","scrolled":false},"outputs":[],"source":"b1 = nn.Sequential(nn.Conv2d(1, 64, kernel_size=7, stride=2, padding=3),\n                   nn.ReLU(),\n                   nn.MaxPool2d(kernel_size=3, stride=2, padding=1))\n\nb2 = nn.Sequential(nn.Conv2d(64, 64, kernel_size=1),\n                   nn.Conv2d(64, 192, kernel_size=3, padding=1),\n                   nn.MaxPool2d(kernel_size=3, stride=2, padding=1))\n\nb3 = nn.Sequential(Inception(192, 64, (96, 128), (16, 32), 32),\n                   Inception(256, 128, (128, 192), (32, 96), 64),\n                   nn.MaxPool2d(kernel_size=3, stride=2, padding=1))\n\nb4 = nn.Sequential(Inception(480, 192, (96, 208), (16, 48), 64),\n                   Inception(512, 160, (112, 224), (24, 64), 64),\n                   Inception(512, 128, (128, 256), (24, 64), 64),\n                   Inception(512, 112, (144, 288), (32, 64), 64),\n                   Inception(528, 256, (160, 320), (32, 128), 128),\n                   nn.MaxPool2d(kernel_size=3, stride=2, padding=1))\n\nb5 = nn.Sequential(Inception(832, 256, (160, 320), (32, 128), 128),\n                   Inception(832, 384, (192, 384), (48, 128), 128),\n                   d2l.GlobalAvgPool2d())\n\nnet = nn.Sequential(b1, b2, b3, b4, b5, \n                    d2l.FlattenLayer(), nn.Linear(1024, 10))\n\nnet = nn.Sequential(b1, b2, b3, b4, b5, d2l.FlattenLayer(), nn.Linear(1024, 10))\n\nX = torch.rand(1, 1, 96, 96)\n\nfor blk in net.children(): \n    X = blk(X)\n    print('output shape: ', X.shape)\n\n#batchsize=128\nbatch_size = 16\n# 如出现“out of memory”的报错信息，可减小batch_size或resize\n#train_iter, test_iter = d2l.load_data_fashion_mnist(batch_size, resize=96)\n\nlr, num_epochs = 0.001, 5\noptimizer = torch.optim.Adam(net.parameters(), lr=lr)\nd2l.train_ch5(net, train_iter, test_iter, batch_size, optimizer, device, num_epochs)"}],"metadata":{"kernelspec":{"name":"python3","display_name":"Python 3","language":"python"},"language_info":{"name":"python","version":"3.7.3","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}